Development of Automated Robotic Microassembly for Three ......Lidai Wang Doctor of Philosophy...

Development of Automated Robotic Microassembly for Three-Dimensional Microsystems

by

Lidai Wang

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Department of Mechanical and Industrial Engineering University of Toronto

© Copyright by Lidai Wang 2009

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Development of Automated Robotic Microassembly for

Three-Dimensional Microsystems

Lidai Wang

Doctor of Philosophy

Department of Mechanical and Industrial Engineering University of Toronto

2009

Abstract

Robotic microassembly is a process to leverage intelligent micro-robotic technologies to

manipulate and assemble three-dimensional complex micro-electromechanical systems (MEMS)

from a set of simple-functional microparts or subsystems. As the development of micro and

nano-technologies has progressed in recent years, complex and highly integrated micro-devices

are required. Microassembly will certainly play an important role in the fabrication of the next

generation of MEMS devices. This work provides advances in robotic microassembly of

complex three-dimensional MEMS devices. The following key technologies in robotic

microassembly are studied in this research: (i) the design of micro-fasteners with high accuracy,

high mechanical strength, and reliable electrical connection, (ii) the development of a

microassembly strategy that permits the manipulation of microparts with multiple degrees of

freedom (DOFs) and high accuracy, (iii) fully automated microassembly based on computer

vision, (iv) micro-force sensor design for microassembly. An adhesive mechanical micro-

fastener is developed to assemble micro-devices. Hybrid microassembly strategy, which consists

of pick-and-place and pushing-based manipulations, is employed to assemble three-dimensional

micro-devices with high flexibility and high accuracy. Novel three-dimensional rotary MEMS

mirrors have been successfully assembled using the proposed micro-fastener and manipulation

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strategy. Fully automatic pick-and-place microassembly is successfully developed based on

visual servo control. A vision-based contact sensor is developed and applied to automatic micro-

joining tasks. Experimental results show that automatic microassembly has achieved sub-micron

accuracy, high efficiency, and high success rate. This work has provided an effective approach to

construct the next generation of MEMS devices with high performance, high efficiency, and low

cost.

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Acknowledgments I would like to express my deep thanks to my academic supervisors, Professor James K.

Mills, and Professor William L. Cleghorn for all their advices and guidance during all phases of

my doctoral research. Professor Mills and Professor Cleghorn are great supervisors who have

given me excellent suggestions, insightful criticism, and full support for this research. I also

thank them for providing enormous help on the paper publish and thesis preparation.

I also would like to thank Dr. Foued Ben Amara and Dr. Jean W. Zu for their helpful insight

and suggestions in this research.

I would like to thank my friends and colleagues at the Laboratory for Nonlinear Systems

Control, Lu Ren, Yasser Anis, Henry Chu, Xiaoyun Wang, Xuping Zhang, Joel and others, for

their input and encouragement.

I would like to thank my dearest wife Wei, for her love, sacrifice, and encouragement. This

work would not have been feasible without the love and support from my brother and my

parents.

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Table of Contents Abstract……………………………………………………………………………………………ii

Acknowledgments……………………………………………………..…………………………iv

Table of Contents………………………………………………………………………………….v

List of Tables …………………………………………………………………………………...viii

List of Figures…………………………………………………………………………………….ix

Nomenclature…………………………………………………………………………………….xii

Chapter 1 Introduction………………………………………………………………………….1

1.1 Motivation of microassembly…………………………………………………………1

1.2 Literature survey………………………………………………………………………3

1.2.1 Microassembly approaches: parallel versus serial………………………...3

1.2.2 Active and Passive Microgripper………………………………………….4

1.2.3 Micro-fastener techniques…………………………………………………5

1.2.4 Micromanipulation strategies……………………………………………...7

1.2.5 Micro-force measurement and contact detection………………………….8

1.2.6 Automation of microassembly…………………………………………….9

1.3 Research objectives………………………………………………………………….12

Chapter 2 Microassembly System……………………………………………………………..13

2.1 Micro-robotic workstation ……………………………..……………………………13

2.2 Motorized video microscopy system………………………………………………...13

vi

2.3 Motion control system……………………………………………………………….14

2.4 Adhesive bonding microgripper……………………………………………………..17

2.5 Robotic system calibration………………………………………….………………..18

Chapter 3 Adhesive Mechanical Micro-Fastener Design ……………………………..……..23

3.1 Design of adhesive mechanical micro-fastener…..…………………………….……23

3.1.1 Self-alignment mechanism design……………………………………….24

3.1.2 Adhesive droplet manipulation…………………………………………..25

3.2 Microassembly of MEMS devices using adhesive mechanical fastener…………….29

Chapter 4 Hybrid Micromanipulation Strategy ………………………….…………..……...34

4.1 Hybrid micromanipulation strategy ……………...…………………………….……34

4.2 Microassembly of three-dimensional rotary mirror………………………………….39

4.2.1 Architecture of three-dimensional rotary MEMS mirror………………...39

4.2.2 Microparts design for rotary MEMS mirror……………………………..43

4.2.3 Hybrid microassembly procedures………………………………………46

Chapter 5 Vision-Based Automated Microassembly…………………….…………..…….…57

5.1 Procedures of automated pick-and-place microassembly…...………………….……57

5.2 Three-stage automated micrograsping strategy……………………………………...60

5.3 Coarse-to-fine visual servo control…………………………………………………..65

5.4 Experiments on automated micro-grasping………………………………………….69

5.5 Two-stage automated micro-joining strategy………………………………………..75

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5.6 Auto-focus on reoriented micropart………………………………………………….76

5.7 Contact sensor for three-dimensional micro-joining………………………………...79

5.8 Experiments on automated micro-joining……………………………………………82

Chapter 6 Micro-Force Sensor Design for Microassembly .…………….…………..…….…86

6.1 Principle of electron tunneling micro-force sensor …...……….……………….……86

6.2 Micro-force sensor design based on PolyMUMPs…………………………………..88

6.3 Micro-force sensor design based on SOIMUMPs…………………………………...96

Chapter 7 Conclusion and Discussions…………………….…………….…………..………105

7.1 Thesis summary …...……….……………….……………………………………...105

7.2 Summary of contributions…………………………………………………………..109

7.3 Recommendations for future work…………………………………………………111

References……………………………………………………………………………………...113

viii

List of Tables Table I Parmetres of microgripper……………………………………………………………91

Table II Response of thermal actuator.………………………………………………………...91

Table III Parmetres of compliant beams in pushing probe…………………………………….100

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List of Figures Figure 1-1 Passive microgripper and micropart…………………………………………………..5

Figure 2-1 Micro-robotic workstation for use in microassembly………………………………..14

Figure 2-2 Motion control system………………………………………………………………..15

Figure 2-3 Microassembly workstation user interface…………………………………………...15

Figure 2-4 Designation of micropart and target position based on CAD model………………...16

Figure 2-5 Coordinates in robotic microassembly system……………………………………….19

Figure 3-1 Chamfered peg-hole mechanism……………………………………………………..24

Figure 3-2 Snap-lock joint mechanism…………………………………………………………..25

Figure 3-3 Liquid droplets on micro-tip surfaces………………………………………………..26

Figure 3-4 Design of micro-probe for adhesive droplet manipulation…………………………..27

Figure 3-5 Micro-probes with different sizes……………………………………………………27

Figure 3-6 Manipulate adhesive droplets with different sizes…………………………………...28

Figure 3-7 Relation between droplet size and deposit tip area…………………………………..29

Figure 3-8 Microassembly of a micropart using adhesive mechanical fastener…………………31

Figure 3-9 Assembled micropart using adhesive mechanical fastener…………………………..32

Figure 4-1 Finely adjust orientation of micropart………………………………………………..36

Figure 4-2 Top edge detection using computer vision…………………………………………...39

Figure 4-3 An N×M optical switch constructed with 1×N and 1×M optical switches…………..40

Figure 4-4 Schematic diagram of a 1×N rotary optical switch…………………………………..43

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Figure 4-5 An adhesive mechanical fastener for rotary MEMS mirror………………………….45

Figure 4-6 Side view of an assembled micro-mirror…………………………………………….46

Figure 4-7 Micromanipulation of adhesive droplets for micro-mirror assembly………………..48

Figure 4-8 Sequential microscopic images in pick-and-place a micro-mirror…………………..50

Figure 4-9 Orientation of assembled micro-mirror………………………………………………51

Figure 4-10 Displacement of slot and mirror top edge during pushing………………………….54

Figure 4-11 Inclination angle of micro-mirror plate during pushing…………………………….55

Figure 4-12 Assembled rotary MEMS mirror…………………………………………………...56

Figure 5-1 Procedures of automated pick-and-place microassembly……………………………60

Figure 5-2 Passive microgripper and micropart………………………………………………….61

Figure 5-3 Flow chart of automated micrograsping in three-dimensional space………………...62

Figure 5-4 Side view of alignment in the z-axis direction……………………………………….64

Figure 5-5 Automated micrograsping procedures……………………………………………….72

Figure 5-6 Output signal of fine alignment controller…………………………………………...73

Figure 5-7 Jaw deflections and alignment error with fine visual servo control………………….73

Figure 5-8 Jaw deflections and alignment error without fine visual servo control……………...74

Figure 5-9 Contour feature extraction for reoriented micropart…………………………………77

Figure 5-10 Gradient of focus value……………………………………………………………..78

Figure 5-11 Cross section of snap-lock joint feature…………………………………………….79

Figure 5-12 Variations of images during insertion………………………………………………81

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Figure 5-13 Contact value curve during insertion……………………………………………….81

Figure 5-14 Patterns of reoriented micropart and base structure………………………………...82

Figure 5-15 Automated micro-joining in three-dimensional space……………………………...83

Figure 5-16 Automated joined micropart…………………………………………………...…...84

Figure 6-1 Structure of an electron tunnel……………………………………………………….88

Figure 6-2 Passive microgripper with two electron tunneling micro-force sensors……………..89

Figure 6-3 U-beam thermal actuator……………………………………………………………..90

Figure 6-4 Thermal actuator deflections…………………………………………………………92

Figure 6-5 Feedback controller for electron tunneling micro-force sensor……………………...93

Figure 6-6 Current amplifier for electron tunneling force sensor………………………………..93

Figure 6-7 Microgripper integrated with micro-force sensors…………………………………...94

Figure 6-8 Design of tunnel tips, (a) right angle, (b) acute angle………………………………..95

Figure 6-9 Fabricated tunnel tips, left: right angle, right: cute angle……………………...…….95

Figure 6-10 Cut through features for extending out pushing probe……………………………...97

Figure 6-11 Pushing probe integrated with electron tunneling micro-force sensor……………...98

Figure 6-12 Compliant beam dimension in micro-force sensor…………………………………99

Figure 6-13 Design and fabrication of electron tunneling tips…………………………………101

Figure 6-14 Sidewalls of electrodes……………………….……………………………………102

Figure 6-15 Focused ion beam coating on sidewall of electrode………………………………103

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Nomenclature Acronyms

C c programming language

CAD computer aided design

CCD charge-coupled device

DC direct current

DLL dynamic-link library

DOF degree of freedom

DRIE deep reactive-ion etching

FIB focused ion beam

LED light-emitting diode

LabVIEW labview programming language

MEMS microelectromechanical systems

MUMPs multi-user MEMS processes

PID proportional–integral–derivative controller

SOI silicon on isolator

SEM scanning electron microscopy

UV ultraviolet

VDM vision development module

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General symbols

d electron tunnel width

E Young’s modulus

fx digital resolution of microscope in x-axis direction

fy digital resolution of microscope in y-axis direction

Fc capacitive force

Fe external force

Fy force exerted on microgripper in y-axis direction

G gradient value

G average gray value of the interested image

i electron tunneling current

k coefficient that converts microns to pixels

kc proportional gain in coarse alignment

kp proportional gain in fine alignment

l length of micropart

lT target distance from micropart to microgripper in x-axis direction

m magnification of the microscope objective lens

yM driving torque exerted by the pushing probe

0yM torque from surface tension of adhesive droplet

ip gray value of ith pixel

xiv

p average pixel value

Pr point matrix in robot coordinates

Pi point matrix in image coordinates

Rx effective resistance of electron tunnel

Rf feedback resistance

R rotation matrix between robot coordinates and image coordinates

R21 2nd row 1st column element in the rotation matrix

R22 2nd row 2nd column element in the rotation matrix

s centre point of a slot in snap-lock mechanism

t central point of the top edge of micro-part

st thickness of base structure in a snap-lock mechanism

t’ project of point t on the top surface plane of the rotary motor

uy output signal of coarse alignment controller in y-axis direction

u’y output signal of coarse alignment controller with pattern-selection errors

vy output signal of fine alignment controller in y-axis direction

v’y output signal of fine alignment controller in with pattern-selection errors

sw width of slot in a snap-lock mechanism

mw thickness of micro-mirror

x x translational axis in micro-robotic workstation

xr x coordinate in robot coordinates

xv

xi x coordinate in image coordinates

xs x coordinate of point s in image coordinates

xt x coordinate of point t in image coordinates

xe encoder position in x-axis direction

xp micropart coordinate in x-axis direction in image coordinates

xuj microgripper upper jaw position in x-axis direction in image coordinates

xlj microgripper lower jaw position in x-axis direction in image coordinates

xj centre position of microgripper jaws in x-axis direction in image coordinates

xc target position of micropart in x-axis direction in image coordinates

y y translational axis in micro-robotic workstation

yr y coordinate in robot coordinates

yi y coordinate in robot coordinates

ys y coordinate of point s in image coordinates

yt y coordinate of point t in image coordinates

ye encoder position in y-axis direction

yp micropart coordinate in y-axis direction in image coordinates

yuj microgripper upper jaw position in y-axis direction in image coordinates

ylj microgripper lower jaw position in y-axis direction in image coordinates

yj centre position of microgripper jaws in y-axis direction in image coordinates

yc target position of micropart in y-axis direction in image coordinates

xvi

z z translational axis in micro-robotic workstation

α α rotational axis in micro-robotic workstation

β β rotational axis in micro-robotic workstation

γ γ rotational axis in micro-robotic workstation

θ inclination angle of an assembled micropart

θx misalignment angle between xr and xi axes

θy misalignment angle between yr and yi axes

δx displacement interval between CCD pixels in xi-axis direction

δy displacement interval between CCD pixels in yi-axis direction

ε permittivity of air

1

Chapter 1

Introduction

1.1 Motivation of microassembly

As the development of micro and nano-technologies has progressed in recent years,

the next generation of micro-devices, require complex structures; utilize hybrid materials;

have high integration densities; and have multiple functions. Examples of these emerging

micro-devices include three-dimensional microelectrode array [1], Fourier transform

micro-spectrometer [2], and three-dimensional micro-coils [3]. Compared with

conventional micro-devices, these novel micro-devices may have higher aspect ratios,

more types of materials, higher integration densities, and more complex structures.

Therefore, the next generation of micro-devices may have the potential to achieve unique

functions with high performance. Conventional micromachining technology has utilized

monolithically fabricated micro-devices with low aspect ratios, limited types of materials,

and simple functions. Even though custom fabrication processes might be able to

fabricate certain complex micro-devices monolithically, expensive fabrication costs

would make devices fabricated in this manner commercially unviable. New fabrication

technologies are required to construct the next generation of micro-devices.

Microassembly is an emerging technology that leverages micro-robots to assemble

complex micro-devices from a set of microparts or subsystems. Out of necessity, these

microparts or subsystems are fabricated with different fabrication processes and materials.

These fabrication processes and materials are incompatible, hence that they cannot be

fabricated monolithically. These microparts may also have low aspect ratios or simple

functions. Microassembly has the capability to manipulate these microparts or

Chapter 1 Introduction 2

subsystems, and join them together to construct unique micro-devices with hybrid

materials, incompatible fabrication processes, high aspect ratios, and complex functions.

Therefore, microassembly is a promising approach to construct the next generation of

micro-devices.

Prior to commercial success of microassembly technology, three major challenges

must be resolved:

1. Micro-fastener design that can be used to join microparts together, with low

complexity, high mechanical strength, and reliable electrical connection.

2. Micromanipulation strategies that allow for global manipulation of microparts in

multiple degrees of freedom, with high positioning accuracy.

3. Full automation of microassembly with high accuracy, high productivity, and high

success rate.

The first challenge in microassembly is to design suitable micro-fasteners to join

microparts. These micro-fasteners must have simple structures, which would greatly

simplify assembly operations, lower the cost, and make them suitable for automatic

microassembly. Strong mechanical connection and reliable electrical connection are also

very important to assemble functional micro-devices. To construct complex micro-

devices, global manipulation of microparts is necessary. At the same time, the assembled

microparts must be placed at designated positions and orientations with high accuracy.

Manual operations in microassembly tasks suffer from high cost, limited accuracy, and

poor reliability. Hence, full automation of microassembly must be accomplished to

increase the accuracy, productivity, success rate, and lower the assembly cost.


1.2 Literature survey

1.2.1 Microassembly approaches: parallel versus serial

Microassembly can be defined as a micro-manufacturing process in which microparts

from sub-millimeter to sub-micrometer scale are manipulated and assembled to create

micro-devices. Microassembly techniques may be categorized into two approaches. One

approach is referred to as parallel microassembly, which allows for simultaneous

manipulation of a batch of microparts. Examples of parallel microassembly include flip-

chip wafer-level transfer [4], self-microassembly using heating effects [5, 6], centrifugal

forces [7], magnetic forces [8], and electrostatic forces [9]. Because multiple microparts

can be manipulated at the same time, parallel microassembly has the potential to achieve

high productivity. However, limited by simultaneous manipulation, parallel

microassembly lacks the capability to perform complex micromanipulation tasks, such as

global translation and rotation of microparts with multiple degrees of freedom, or

attachment of one microparts to another assembled microparts. The other approach is

referred to as serial microassembly, in which microparts are assembled one by one, in a

sequential manner. Since most serial microassembly tasks are carried out using micro-

robots, serial microassembly is also referred to as robotic microassembly. Examples of

robotic microassembly systems have been described in [10-12]. Compared with parallel

approach, serial microassembly has the capability to manipulate microparts to arbitrary

positions and orientations. Hence, serial microassembly is more suitable to construct

complex micro-devices. This work focuses on the development of serial microassembly

technologies. In the following sections, literatures relevant to serial microassembly

technologies are examined.


1.2.2 Active and Passive Microgripper

Microgrippers are indispensable tools to manipulate and assemble microparts. Many

types of microgrippers have been developed for use in microassembly systems. One of

the most common microgripper designs includes two or more micro-fingers and a set of

actuators. In order to manipulate microparts, the actuators drive the micro-fingers to open

and close. Thus, this type of microgripper is referred to as an active microgripper.

Different types of actuators have been employed in the active microgrippers, such as

piezoelectric actuators [13-16], electrostatic actuators [17-18], electro-thermal actuators

[19-21], shape-memory-alloy [22, 23]. An active microgripper is able to grasp irregular-

shaped microparts, and control the forces exerted on the grasped microparts. Another

type of microgripper, which is referred to as passive microgripper, does not rely on any

actuators, but employs elastic deflection forces to hold microparts. An example of the

passive microgripper has been presented in [24], where DRIE etching process was

employed to fabricate the interface features on the passive microgripper and microparts.

Another passive microgripper has been developed by Dechev et al. [3]. PolyMUMPs, a

surface micromachining MEMS fabrication process, was utilized to fabricate the passive

microgripper and the grasping features on microparts. As shown in figure 1-1 [3], the

interface features on the passive microgripper and the micropart have a two-layer

interlock structure, which prevent the rotations of the grasped micropart. The elimination

of actuators in passive microgrippers makes it easy and robust to grasp a micropart. One

limitation of this passive approach is that the micropart must maintain reaction forces

towards or opposite to the motion of microgripper during the grasping and releasing

operations. And the grasping features must be fabricated onto the microparts. Hence, the


active microgripper is more dexterous, and capable of manipulating various shapes of

microparts. But for specific microassembly tasks, a passive microgripper can provide

more easy and robust solution. In this work, the passive microgripper developed by

Dechev et al. [3] is employed to assemble microparts. The proposed methodologies in

this work could also be used for other microassembly tasks with either passive

microgrippers or active microgrippers.

Figure 1-1 Passive microgripper and micropart [3]

1.2.3 Micro-fastener techniques

Microassembly requires the design of micro-fastener that joins two microparts

together. The micro-fastener should be able to provide high assembly accuracy, a strong

mechanical connection, and a reliable electrical connection between the assembled

microparts. In addition, the micro-fastener should be easy to assemble, which is critical to

automated microassembly. To date, various micro-fastener designs have been proposed to

assemble microparts. Snap-lock micro-fasteners, which rely on elastic deflections of


compliant beams, have been studied in [25-27]. Key-lock and inter-lock mechanical

fasteners have been studied in [27]. These mechanical fasteners can achieve high

positioning accuracy in certain directions. For example, in a snap-lock micro-fastener, the

join features on two mating microparts are accurately aligned under elastic deflection

forces. The mechanical strength in other directions might not be high enough to prevent

the rotation of assembled microparts. Another problem is high contact resistances which

may exist between two mating microparts, which leads to a poor electrical connection. To

increase the mechanical strength and the electrical connection of the micro-fastener, an

active micro-fastener has been developed by Zhang et al. [28]. A slot on one micropart

could open up with the use of thermal actuators, and close after another micropart is

joined. A tight joint is created with the assistance of actuators. However, the employment

of actuators in the micro-fastener increases the complexity and the fabrication cost, and

an active micro-fastener is only applicable in some specific microassembly tasks. For

example, it is too difficult to join one micropart onto another assembled micropart using

this type of active micro-fastener. Another type of micro-fastener is a shear-lock micro-

fastener that employs plastic deformations of a fastener tip to create a joint [29]. Sub-

millimeter-sized rigid blocks have been assembled using UV-curable adhesive in [30].

Each block is dipped into the adhesive, placed into a designated position, and cured while

being held into the position by tweezers. The adhesive bonding method is able to provide

a strong mechanical connection and a reliable electrical connection between assembled

microparts, but the alignment accuracy might be affected by the surface tension of the

adhesive. Hence, novel design of micro-fastener that is able to provide high accuracy,

great mechanical and electrical connection between the assembled microparts is required.


1.2.4 Micromanipulation strategies

Microassembly tasks need micromanipulation strategies that are capable of

manipulating microparts with multiple degrees of freedom and high positioning accuracy.

The pick-and-place micromanipulation strategy [3, 31, 32] has been broadly applied in

sequential microassembly. This method often utilizes a microgripper to grasp, translate,

reorient, and join a micropart to other microparts. This approach is suitable for global

manipulation of microparts with multiple degrees of freedom. Another

micromanipulation strategy is pushing-based approach [33, 34], which uses micro-probes

to push microparts to adjust their positions and orientations. This pushing-based

microassembly strategy can only adjust the positions or orientations of the manipulated

micropart with limited degrees of freedom. It is difficult to globally translate and re-

orient the micropart. But the pushing-based manipulation is capable to reach higher

positioning accuracy than the pick-and-place microassembly.

Instead of gravitational force dominating at the macro-scale, stiction forces, such as

electrostatic, Van der Waals, and surface tension forces, play more important roles at the

micro-scale. In micromanipulation operations, release of microparts from a microgripper

or micro-probe is a challenging problem due to these stiction forces. Many approaches

have been proposed to release manipulated microparts, such as vibration of the

microgripper [35], pushing microparts with a needle [36], or injection of gas to push the

micropart [36]. But in microassembly, manipulated microparts are to be fixed onto

another microparts before release from microgripper. For instance, manipulated

microparts are joined to other micro-structures through the use of adhesive bonding [30]

or mechanical fasteners [25-28]. As long as the fixture strength of the micro-fasten is


higher than the stiction forces between the microgripper and grasped microparts, the

stiction forces will not affect the release of the microparts from the microgripper.

1.2.5 Micro-force measurement and contact detection

Measurement of interaction forces and contact states in microassembly process is

important to prevent collisions or damages, minimize the interaction forces, and

accurately align microparts. Micro-forces in microassembly may be as large as several

milli-Newtons. Several types of micro-force sensors have been developed for use in

microassembly and micromanipulation systems, such as piezoresistive [32, 37-39],

piezoelectric [40, 41], capacitive [42], vision-based [33, 43, 44], and optical [45] micro-

force sensors. Piezoresistive and piezoelectric micro-force sensors are often integrated

into microassembly systems through two approaches: attachment of microgrippers onto

macro-sized piezoresistive or piezoelectric force sensors, or fabrication of micro-force

sensors into the micro-grippers. Since inertial forces and vibrations in the environment

always exist, the resolution of micro-force sensors using the first approach is very limited.

Even though vibration isolation devices are capable of attenuating some component of

the environmental disturbances, the vibrations from the environment cannot be fully

isolated. In the second approach, because the masses attached to the micro-force sensors

are micro-scale, the micro-force sensors may obtain greater force resolution than that in

the first approach. However, integration of piezoresistive and piezoelectric micro-force

sensors into the microgrippers requires complex fabrication processes, which are

expensive and not always applicable. Compared with piezoresistive and piezoelectric

force sensors, capacitive micro-force sensors are easier to integrate with microgrippers.

But the sensitivity of these sensors is proportional to the area of the capacitor, which is


limited by the size of the silicon chip. Although through the use of a high gain amplifier,

the sensitivity of the capacitive force sensor can be improved, the electronic noise is also

amplified. The minimum detectable force is determined by the electronic background

noise and the system bandwidth. Vision-based micro-force sensors rely on microscopy

vision, in which the resolution of the force measurement is limited by the optical

resolution. Moreover, vision-based micro-force sensors have low sample rates and

requires microscope focusing on the deflected micro-features. The optical beam

deflection force sensor has the potential to achieve a very high sensitivity, however, this

type of micro-force sensor has a relatively complex structure; and precise calibration is

required to align the optical beam with the deflection cantilever. Micro-force sensors can

also be used to detect contact states between microparts, but contact sensors may have

simpler structure than force sensors, which make it easier to integrate them into

microassembly systems. An electrical contact sensor integrated with passive microgripper

has been employed in a microassembly system in [24].

1.2.6 Automation of microassembly

Full automation is necessary for microassembly to increase the accuracy, productivity,

success rate, and cost efficiency of the microassembly process. In macro-scale assembly

operations, kinematic calibration of open-loop assembly systems are in common use in

industrial assembly manufacturing. While there are many common elements in a

microassembly system, far higher (i.e., micron or sub-micron) accuracy is required.

Kinematic model calibration, at the micro-scale, is significantly affected by thermal

growth errors. Common thermal compensation techniques are expensive to implement

and inefficient [10]. On the other hand, stiction effects in the micro-world [46] also


increase the uncertainty in localizing micro-components. Hence, determining the initial

positions of MEMS components, coupled with open loop control may be problematic in

microassembly, and may lead to significant unresolved implementation issues. Kinematic

errors may arise from thermal expansion effects, part movement during assembly, and a

number of other factors. Hence, the use of closed-loop control provides one solution to

achievement of automatic microassembly. In order to automatically perform

microassembly tasks, accurate measurement and control of the positions of microparts in

three-dimensional space is required.

Computer vision is a flexible, non-contact approach to measure the positions of

microparts, and has been broadly employed in tele-operated and automated

microassembly systems. In order to achieve high assembly accuracy, a high-

magnification microscopy vision system is often used to take the images of the micro-

components with micron or sub-micron resolution. The basic limitation for a high-

magnification optical microscope is the low depth of field [10]. Depth of field is defined

as the distance in front of, or behind, the subject that appears to be in focus. Objects

located outside of depth of field result in blurred images of three-dimensional MEMS

structures. To address this problem, an active zooming method [47] has been used to

adjust the magnification of microscope. But as the depth of field increases, the optical

resolution of the microscope decreases. Moreover, it is not time-efficient to frequently

adjust the magnification. Another approach to extend the depth of field is using camera

array that has multiple cameras with different magnifications [10]. But camera array

would increase the cost and limit the working space of the microassembly workstation.

Other approaches to resolve the issue of low depth of field include stereomicroscopy


technology [48, 49], depth-from-focus method [10, 50-52], and image synthesis method

based on models of microscope and micropart [53]. However, these methods still cannot

fully address the issue of low depth of field in automated microassembly.

Vision-based automated control has been employed in automated microassembly

systems [10, 31, 33, 50-53]. Visual servo control can be categorized into either image-

based or position-based approaches. In position-based visual servo control, features of

target object are extracted from computer images, followed by pose estimation, which

determines the pose of the target object with respect to the camera. The signal utilized for

feedback is the pose error of the target object being imaged. In image-based visual servo

control, the feedback signal is the measured errors of the features in the image, rather

than the pose errors of the target object. An image-based approach may reduce

computational time, but it presents a significant challenge to controller design, since the

visual servo control system is nonlinear, and the pose estimation and controller design are

highly coupled. With increasing computational speed of computers, the execution times

of various image-processing algorithms have become less of a constraint on algorithm

design. Further, position-based control makes the control problem independent of the

vision-based pose estimation.

Another approach in automated microassembly is based on force feedback. Several

micromanipulation systems have employed micro-force sensors as feedback sources [13,

31, 32, 34, 37, 39, 41, 45]. Force-based microassembly does not have the limitation of

low depth of field, and this approach is capable to update the control loop at a higher rate

than the vision-based feedback approach. However, force-based automated


microassembly is not as flexible as visual servo control. Moreover, micro fabrication

processes may limit the integration of micro-force sensors with microgripper.

1.3 Research objectives

This work focuses on the key technologies in microassembly, to facilitate fabrication

of the next generation of micro-devices in a precise, reliable, and low-cost manner. Based

on the challenges in current microassembly technologies, the objectives of this research

work are

(1) To develop micro-fastener that allows for joining micropart with a

simple structure, high mechanical strength, and reliable electrical

connection.

(2) To study the micro-manipulation strategy that is able to manipulate

microparts with high flexibility, high accuracy, and low complexity.

(3) To demonstrate the fabrication ability of microassembly by assembly

of complex three-dimensional micro-devices.

(4) To develop high accuracy contact sensor for automated microassembly.

(5) To study the automated control technologies that control a micro-robot

to fully automate assemble microparts in three-dimensional space.

(6) To investigate micro-force sensor design for microassembly.

13

Chapter 2

Microassembly System

This chapter introduces the microassembly system used in this research work,

including the micro-robotic workstation, video microscopy system, motion control

system, and some background materials needed to complete the microassembly tasks.

2.1 Micro-robotic workstation

A micro-robotic workstation, developed by Dechev et al. [12], is utilized in this work

to perform microassembly tasks. An overview description of the micro-robot is provided

here, with the detailed information given in [12]. Figure 2-1 shows the structure of the

micro- robotic workstation. Six stepper motors are employed to drive six axes (α, β, γ, x,

y and z). The micro-robot is capable to manipulate microparts with six degrees of

freedom. The three rotational axes (α, β, γ) have angular resolutions of 0.2 degrees. The x,

y and z axes have linear displacement resolutions of 0.2 μm. Three linear encoders with

resolutions of 0.1 μm are mounted to the three translational axes to measure the absolute

displacements of the platform. A MEMS chip, on which the microparts are located, is

mounted on top of the worktable. A microgripper is bonded to the free end of a probe.

2.2 Motorized video microscopy system

A motorized video microscopy system provides vision-based feedback signals during

the microassembly operations. This system utilizes an Infinitube and a Nikon CFI60 L

Plan Epi 20× objective lens, with depth of field of 1.5 μm. An ultra-bright green LED

(light emitting diode) provides co-axial in-line illumination for the MEMS chip. A

monochrome video camera (Pixelink PL-A741) is used with a 2/3” CCD and a highest

Chapter 2 Microassembly System 14

resolution of 1280×1024 pixels. The pixel size of the CCD camera is 6.7×6.7 μm. The

optical resolution of the entire microscopy system is approximately 0.9 μm, and the

digital resolution is 0.33 μm. This microscopy system was first developed by Dechev et

al., and mounted on a manual stage [12]. In order to automate the microassembly, a

motorized three-axis (xc, yc and zc) translation stage (Thorlabs PT3) and three stepper

motors (Thorlabs ZST25B) are employed in this work. Three micro-stepping motor

drivers (A3967SLB) are employed to drive the motors, which allow the microscope

translating in three coordinate directions with a resolution of 0.274 μm.

Figure 2-1 Micro-robotic workstation for use in microassembly

2.3 Motion control system

A schematic diagram of the motion control system for microassembly is shown in

figure 2-2. The video microscopy system is the main feedback source for human

supervision and automated control. The video camera is connected to a PC through a

1394 bus. Motion commands are sent to two motion control cards (model # Galil DMC-

1800), and the corresponding motions are executed on the robotic manipulator. A visual

control program was developed in NI LabVIEW, NI Vision Development Module

(version 8.2), and C language. The interface to motion control cards are developed in C


language, and then compiled into DLL (dynamic-link library) files. The LabVIEW visual

control program calls the functions in the DLL files to communicate with the motion

control cards. Image processing and motion control programs were written in LabVIEW.

Figure 2-3 shows the user interface of the microassembly motion software. An operator

can monitor the microassembly process through the microscopy image window. Tele-

operation and auto- assembly functions are provided to manipulate and assemble

microparts.

Figure 2-2 Motion control system

Figure 2-3 Microassembly workstation user interface


Figure 2-4 Designation of micropart and target position based on CAD model

As shown in figure 2-4, the motion control program allows an operator designating a

micropart and its target assembly position. The CAD model of the MEMS chip is loaded

to the program. The operator may pick up the coordinates of the micropart, and then

specify its target position. After manual initial alignment of the MEMS chip with the

microscopy system, the designated micropart may be brought into the field of view of the

microscope through the use of open-loop control.


2.4 Adhesive bonding microgripper

In this work, a passive microgripper made from PolyMUMPs micromachining

process was employed to grasp microparts. Bonding the microgripper onto the robotic

manipulator is the first step towards manipulation and assembly of microparts. In this

work, UV (ultraviolet) curable adhesive (Noland NCA130) was utilized to bond the

microgripper onto the robotic manipulator. As shown in figure 2-1, a single metal probe

(Terra Universal 9111-10) is connected to the robotic manipulator. Prior to adhesive

bonding, the microgripper is fixed onto the substrate of the MEMS chip through a set of

tethers. The steps to bonding a passive microgripper to the free end of the probe are: (1)

applying the proper amount of adhesive to the free end of the probe; (2) aligning the

probe with the bonding pad of the passive microgripper; (3) curing the adhesive; (4)

releasing the microgripper from the MEMS chip by breaking the tethers. In the first step,

the free end of the probe is dipped into an adhesive reservoir by several microns, and then

moved away from the adhesive reservoir. Some adhesive will adhere to the probe. The

amount of adhesive on the probe is critical to the success of adhesive bonding. Too much

adhesive could bond the microgripper onto the substrate of MEMS chip; insufficient

adhesive cannot provide enough force to release the microgripper from the MEMS chip.

In order to control the amount of the adhesive, the size of the free end of the probe should

be in the range of tens of microns. The original probe used in this work has a diameter of

1 μm. When dipping this original probe into the adhesive reservoir, the adhesive would

not remain on the free end of the probe due to the effect of surface tension. To increase

the diameter of the probe, a pair of sharp scissors was used to cut the probe. When the

diameter of the probe is in the range from 30 to 80 μm, the adhesive bonding has a high


chance to succeed. The alignment of the probe with the bonding pad on the microgripper

is manually carried out under an optical microscope. UV light was applied for 120

seconds to cure the adhesive. When releasing the microgripper from the MEMS chips,

the MEMS chips move away from the probe. Because the bonding pad of the

microgripper has adhered to the probe, the tethers would be broken. In order to ensure all

tethers break at the same time and the microgripper does not deviate from its original

position, the operation of tether breaking should be taken place as fast as possible. In this

work, the MEMS chip moved away from the probe at a speed of 2 mm/s, which provided

100% success rate for release of the microgrippers from the MEMS chips.

2.5 Robotic system calibration

Two sets of coordinate systems are attached to the translation axes of the

microassembly robot and the motorized video microscopy system. Manufacture and

assembly errors may lead to misalignment errors between the two sets of coordinates.

The axes in the same set of coordinates might be not perfectly perpendicular to each other

as well. The misalignment may increase the position errors, increase the transit time of

the visual servo control, and even cause microassembly operations to fail. As shown in

figure 2-5, two sets of coordinates are defined. The robot coordinates [ ]Trr yx are

attached to the robotic worktable. The image coordinates [ ]Tii yx are parallel to the plane

of the CCD sensor. Let θx represent the misalignment angle between the xr-axis and xi-

axis, and let θy represent the misalignment angle between the yr-axis and yi-axis. In

automated microassembly tasks, all vision-based measurements will be carried out in the

image coordinates. The measured signals, obtained from the data in image coordinates

are fed back to the microassembly robot, are used to drive the motors in the robot


coordinates. The misalignment between the two sets of coordinates leads to errors. In

order to improve the performance of automated microassembly tasks, the misalignment

between the two sets of coordinates must be calibrated and compensated. The scale

coefficients between the two sets of coordinates must also be calibrated.

Figure 2-5 Coordinates in robotic microassembly system

Here we do not consider the misalignment between the two z-axes in two sets of

coordinates, because the z-axis of the robot system has been carefully adjusted. The

misalignment in the z-axis direction is smaller than 0.05 degrees, which is much smaller

than the misalignments in the other two axes. In this work, the calibration algorithm only

compensates major misalignment errors in the xr- and yr-axis directions. Accurate

calibration of all the errors is not cost-effective. Moreover, thermal expansion and other

unpredictable disturbances from the environment always exist, and cannot be fully

compensated. Therefore, the employment of feedback control to compensate small errors


and other disturbances becomes necessary. But calibration and compensation of the major

errors still help to shorten the time required to achieve adequate positioning accuracy by

feedback control.

The calibrations of misalignment errors and the scale coefficients between the two sets

of coordinates is carried out through a rotation matrix R, which is expressed as

⎥⎦

⎤⎢⎣

⎡θθθ−θ

=yyxy

yxxx

ffff

cossinsincos

R

where fx and fy are the digital resolutions of the microscope in the x and y-axis directions,

representing the scale coefficients. Here, we have:

mf xx δ= , mf yy δ=

where δx and δy are the displacement intervals between the CCD pixels in the xi and yi-

axis directions, and the parameter m is the magnification of the microscope objective lens.

The coordinate transformation from the image coordinates to the robot coordinates is

expressed by

⎥⎦

⎤⎢⎣

⎡=⎥

⎦

⎤⎢⎣

⎡

i

i

r

r

yx

yx

R

In order to accurately control the motion of the microassembly robot from the images

captured by the CCD camera, it is necessary to determine the rotation matrix R. To

calibrate the rotation matrix R, a micro-object is randomly translated in the x-y plane of

the robot coordinates; and n sets of positions of the micro-object in the image coordinates,

denoted as [ ]Tijij yx (j=1,2,...n), are measured using pattern matching method. The

corresponding positions in the robot coordinates, denoted as [ ]Trjrj yx (j=1,2,...n), are

recorded by the linear encoders of the microassembly robot. A multivariable least squares

fit method is employed to solve this problem. Denoting rP and iP as


⎥⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢

⎣

⎡

−−−

−−−

=

∑∑∑

∑∑∑

===

===n

jrjrn

n

jrjr

n

jrjr

n

jrjrn

n

jrjr

n

jrjr

r

yn

yyn

yyn

y

xn

xxn

xxn

x

112

11

112

11

111

111

L

L

P

⎥⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢

⎣

⎡

−−−

−−−

=

∑∑∑

∑∑∑

===

===n

jijin

n

jiji

n

jiji

n

jijin

n

jiji

n

jiji

i

yn

yyn

yyn

y

xn

xxn

xxn

x

112

11

112

11

111

111

L

L

P

the rotation matrix can be determined from

( ) 1−= T

iiTir PPPPR

In order to experimentally calibrate the robotic system, sixteen sets of points are

arbitrarily selected, and their positions in both the image coordinates and the robot

coordinates are determined using the pattern matching method and linear encoders,

respectively. Matrix R was obtained from the above equation as:

⎥⎦

⎤⎢⎣

⎡ −=

3636.00015.00194.03859.0

R

The covariance matrix of the residual errors is

⎥⎦

⎤⎢⎣

⎡=−

0167.00024.00024.00191.0

)cov( ir RPP

To validate the effect of the robotic system calibration, two sets of experiments of the

coarse alignments were conducted. In the first set of experiments, fourteen repetitive tests

with visual servo controls, with the use of the rotation matrix R, were carried out to test

the coarse alignment. All fourteen trials started from the same initial conditions and used

the same gain in the feedback controller. The average time to achieve an alignment was

0.688 seconds, with a standard deviation of 0.214 seconds. In the second set of

experiments, twelve repetitive tests of the visual servo controls were conducted without


the use of rotation matrix R. The initial conditions and the gain were the same as those in

the first set of experiments. The average time required for an alignment was 0.912

seconds, with a standard deviation of 0.209 seconds. The results showed that the robotic

system calibration effectively shortened the required time for the visual servo control.

23

Chapter 3

Adhesive Mechanical Micro-Fastener Design

Design of micro-fastener is the first indispensable task towards successful

microassembly. These micro-fasteners should be able to provide reliable mechanical and

electrical connections between the joined microparts. In addition, the joint features

should be easy to assemble with high accuracy, which is the foundation of automated

microassembly. This chapter presents the design of an adhesive mechanical fastener,

which includes adhesive bonding and self-alignment mechanisms. A micro-probe is

developed to pick up and accurately deposit adhesive droplets to their target locations.

Self-alignment mechanisms are introduced to increase the positioning accuracy. Cured

adhesive is able to keep the assembled micropart into its position and provide a

permanent, strong mechanical joint. Through the use of conductive adhesive, a reliable

electrical connection between the joined microparts may be achieved. The adhesive

mechanical fastener only requires simple assembly operations, and has capability to reach

reliable connections and high positioning accuracy between the assembled microparts.

3.1 Design of adhesive mechanical micro-fastener

The adhesive mechanical micro-fastener consists of an adhesive bonding and a

mechanical joint mechanism. The adhesive bonding provides reliable mechanical and

electrical connections between two mating parts. The mechanical joint mechanism has

the capability to self-align the mating features accurately. In addition, the mechanical

joint is able to provide a temporary mechanical connection between the assembled

microparts, so that the positions and orientations of the assembled microparts can be

further adjusted with high accuracy.

Chapter 3 Adhesive Mechanical Micro-Fastener Design 24

3.1.1 Self-alignment mechanism design

The mechanical micro-joint employs a self-alignment mechanism to accurately

position an assembled micropart. As shown in figure 3-1, a basic self-alignment design is

a chamfered peg-hole mechanism. The chamfered end of the peg makes it easy to insert

into the hole. When an alignment error exists between the peg and hole, the contact

between the chamfered surfaces on the peg and the edges of the hole will correct this

error, and finally make an accurate alignment.

Figure 3-1 Chamfered peg-hole mechanism

Another self-alignment design is a snap-lock mechanism, which has the capability of

self-alignment under elastic deflection forces. Moreover, the snap-lock mechanism may

temporarily keep the joined micropart into its position, so that the micropart can be

released from the microgripper before a permanent mechanical connection is created.

Several designs of snap-lock joint mechanisms have been studied in [25-27]. The design

of snap-lock joint mechanism in this thesis uses the snap-lock joint design in [27]. Figure

3-2 shows the front-view and side-view of a snap-lock joint. A slot is located in the

centre of a base structure. Two tips are connected to the micropart body through two

compliant arms. As the tips are pushed into the slot, the two arms deflect inwards. Forces


between the tips and the slot, generated by the elastic deflection of the two compliant

arms, keep the assembled micropart positioned in the slot. And the snap-lock joint

mechanism also provides self-alignment ability between the mating features.

Figure 3-2 Snap-lock joint mechanism

3.1.2 Adhesive droplet manipulation

To create an adhesive mechanical micro-fastener, manipulation of adhesive droplets

and controlling their sizes is important. In this work, a manipulator is developed to pick

up and deposit adhesive droplets and accurately control their sizes. When a liquid droplet

adheres to a clean solid surface, the effect of surface tension tends to minimize the total

surface energy of the liquid droplet. Since uniform adhesive has constant surface energy

density, the effect of surface tension will minimize the total surface area of the liquid

droplet that adheres to the solid surface. A surface tension phenomenon is that a small

liquid droplet tends to move away from a sharp tip of a micro-probe. As shown in figure

3-3 (a), the liquid droplet has higher surface energy on the sharp end of the tip. Hence,

the droplet tends to move towards the end of the tip with lower surface energy. Note that,

the surface energy curves in figure 3-3 only illustrate the trend of surface energy, but do

not represent the surface energy values in scale. Based on this phenomenon, when

picking up and manipulating an adhesive droplet, the tip shown in figure 3-3 (b) is able to


maintain the adhesive droplet at the wide end of the tip. But the tip in figure 3-3 (b)

cannot accurately control the sizes of manipulated adhesive droplets.

Figure 3-3 Liquid droplets on micro-tip surfaces

As shown in figure 3-4, a micro-probe, which consists of a deposit tip, a thin beam,

and a bonding pad, is designed to manipulate adhesive droplets and control their sizes.

The micro-probe is fabricated with uniform material and process, which ensures the

deposit tip, the thin beam, and the bonding pad have the same surface energy density.

Hence, the surface energy of the droplet is only determined from the geometry of the

micro-probe. In figure 3-4, the width of the thin beam is smaller than the widths of the

deposit tip and the bonding pad. For a unit volume of adhesive, the surface energy of the

adhesive on the thin beam is higher than that on the deposit tip and the bonding pad.

Since the effect of surface tension tends to minimize the surface energy of the adhesive,

the thin beam becomes a high-energy barrier, which remains the adhesive on the deposit

tip. Therefore, the area of the deposit tip determines the size of the manipulated adhesive

droplet.

In this work, the micro-probe is fabricated with the Poly1 layer in PolyMUMPs

micro-fabrication process. The thickness of the micro-probe is 2 μm, which is ideal to


prevent too much adhesive adhering onto the sidewalls of the micro-probe. In order to

test the capability of the micro-probe to control the sizes of adhesive droplets, different

micro-probes are developed with different dimensions. As shown in figure 3-5, the sizes

of the deposit tips vary from 4 to 10 μm.

Figure 3-4 Design of micro-probe for adhesive droplet manipulation

Figure 3-5 Micro-probes with different sizes


Figure 3-6 Manipulate adhesive droplets with different sizes

Figure 3-6 shows the manipulation process to pick up and deposit adhesive droplets

using the micro-probes. The micro-probes are bonded to a micro-robot through a bonding

pad. The deposit tips and partial thin beams are dipped into the adhesive reservoir by


several microns. When the micro-probes move away from the adhesive reservoir, a

certain amount of adhesive adheres to the surfaces of the deposit tips and the thin beams.

Due to the effect of surface tension, the adhesive remains on the deposit tips, rather than

expanding along the thin beams. Figure 3-6 (b) shows the deposited adhesive droplets.

In figure 3-6 (b), the boundaries of the deposited adhesive droplets are labeled with

rectangles. The droplet areas are measured in the image by pixels, and plotted in figure 3-

7. This figure indicates that the size of adhesive droplet is roughly proportional to the

area of deposit tip. And the shape of the deposit tip could affect the size of adhesive

droplet. Hence, the designs of micro-probes with different sizes and shapes of deposit tips

are capable to control the sizes of manipulated adhesive droplets.

y = 0.86 x

0

200

400

600

800

1000

0 200 400 600 800 1000 1200

Deposit Tip Area (pixel^2)

Adhesive Droplet Area

(pixel^2)

Square Tips

Rectangular Tip

Figure 3-7 Relation between droplet size and deposit tip area

3.2 Microassembly of MEMS devices using adhesive mechanical fastener

The basic steps to create a micro-fastener using pick-and-place manipulation strategy

are: (1) grasping a micropart using a microgripper, (2) translating and rotating the

micropart to a designated position and orientation, (3) joining a micropart to another

micropart, and (4) releasing the micropart from the microgripper. In order to assemble a


micropart using the adhesive mechanical fastener, two steps should be added to the basic

pick-and-place process. The first one is to deposit adhesive droplets to their target

locations. The second one is to cure the adhesive to create a permanent mechanical

connection. Therefore, the microassembly process to create an adhesive mechanical

fastener consists of the following six steps:

(1) Depositing proper amount of adhesive droplets to designated locations;

(2) Grasping a micropart using a microgripper;

(3) Translating and rotating the micropart through three-dimensional space;

(4) Joining the micropart onto another micropart to create a mechanical fastener;

(5) Curing the adhesive to create a permanent mechanical connection between the

assembled microparts;

(6) Releasing the micropart from the microgripper.

If the mechanical fastener is capable to maintain the joined micropart into its position,

then steps (5) and (6) are interchangeable. An example is the use of snap-lock joint as the

self-alignment mechanism. The snap-lock joint could temporarily keep the joined

micropart into its position, so that the micropart can be released from the microgripper

before curing the adhesive. One advantage is that the curing could be carried out only

once when multiple microparts are assembled in sequence. Furthermore, the orientation

of the released micropart can be further adjusted before curing.

To demonstrate the feasibility of adhesive mechanical fastener, a micropart is

assembled using the proposed approach. The micropart and its base structure are shown

in figure 3-2. A micro-probe utilized to manipulate adhesive droplet has a square deposit


Figure 3-8 Microassembly of a micropart using adhesive mechanical fastener

tip with size of 10×10 μm. Figure 3-8 shows the microassembly process to create an

adhesive mechanical fastener. In figure 3-8 (a) and (b), the micro-probe picks up two

adhesive droplets and deposits them onto their target locations on the base structure. The

sizes of the adhesive droplets are critical to the success of microassembly. Too much


adhesive would cover the snap-lock hole, which may increase the difficulty of the

microassembly. Insufficient adhesive cannot create a strong mechanical connection

between the assembled microparts. This micro-probe has the capability to control the

sizes of adhesive droplets and deposit them onto their target locations. Note that the

optimized adhesive droplet size can be determined experimentally. The assembled

microparts will also affect the bonding mechanical strength. Larger contact area between

the micropart surface and the adhesive, and rough bonding surface could help to create a

strong mechanical bonding.

In figure 3-8 (c), a designated micropart is grasped with a passive microgripper, and

released from the MEMS chip. Then the grasped micropart is translated to the top of the

target location, and rotated by 100 degrees. In figure 3-8 (e) and (f), the snap-lock

mechanical joint is created, and the adhesive is cured to permanently bond the micropart

and the base structure together.


Figure 3-9 Assembled micropart using adhesive mechanical fastener

Before curing the adhesive, the snap-lock mechanical joint is capable to temporarily

maintain the micropart in position. Hence, the orientation of the assembled micropart

could be further adjusted to rotate around the long axis of the slot. This feature gives

more flexibility of the microassembly operation. Figure 3-9 shows the assembled

micropart.

34

Chapter 4

Hybrid Micromanipulation Strategy

Global manipulation of microparts with high accuracy is of fundamental importance

in microassembly technologies. This chapter presents a novel hybrid micromanipulation

strategy, in which pick-and-place micromanipulation and pushing-based operation are

combined together to accurately position microparts in multiple degrees of freedom.

Pick-and-place manipulation is capable to translate and reorient microparts in three-

dimensional space. Pushing-based manipulation may accurately adjust the positions and

orientations of microparts. A three-dimensional rotary MEMS mirror is assembled using

the hybrid manipulation strategy, which demonstrates the high accuracy and high

flexibility of this approach.

4.1 Hybrid micromanipulation strategy

Pick-and-place micromanipulation is capable to manipulate a micropart with multiple

degrees of freedom. However, since collisions or adhesive forces always exist during

releasing the micropart from a microgripper, the micropart may deviate from its ideal

position. Pushing-based manipulation employs a single probe to finely adjust the

positions and orientations of microparts, but global manipulation of microparts is difficult.

However, it is believed that pushing-based manipulation has the potential to achieve

higher accuracy than pick-and-place manipulation. In order to increase the positioning

accuracy, but not to lose the flexibility, a hybrid manipulation strategy is proposed to

assemble microparts. The hybrid manipulation strategy consists of two sequential sub-

steps: (1) assembly of microparts using pick-and-place operation, (2) fine adjustment of

the positions and orientations of microparts using pushing-based manipulation.

Chapter 4 Hybrid Micromanipulation Strategy 35

In order to assemble microparts using the hybrid manipulation strategy, the fastener

between two mating parts must fulfill the following criteria:

(1) The grasped micropart must be able to be released from the microgripper at

the end of the pick-and-place manipulation.

(2) The released micropart must be maintained at its position and allow for further

fine adjustments.

(3) The fastener must be capable to permanently join the assembled microparts

after the pushing-based manipulation.

The adhesive mechanical fastener introduced in Chapter 3 is capable to fulfill the

above requirements. A snap-lock mechanism may temporarily join the microparts, and

allow for release of micropart from the microgripper at the end of the pick-and-place

manipulation. At the end of the hybrid manipulation, the adhesive may be cured to create

a permanent adhesive bonding.

The process to assemble a micropart using the hybrid manipulation strategy and the

adhesive mechanical fastener consists of the following steps:

(1) Depositing adhesive droplets to their target locations;

(2) Globally manipulating a micropart using pick-and-place operation;

(3) Pushing the joined micropart to finely adjust its position and orientation;

(4) Curing the adhesive to create an adhesive bonding.

The deposition of adhesive droplets has been addressed in Chapter 3. General

procedures for global manipulation of a micropart using pick-and-place operation is: (1)

grasping a micropart using a microgripper, (2) translating and rotating the micropart

through three-dimensional space, (3) joining the micropart to a designated target


micropart, and (4) releasing the micropart from the microgripper. The released micropart

might deviate from its ideal position, due to adhesive forces or other disturbances during

the releasing operation. The followed pushing-based manipulation is capable to finely

adjust the position and orientation of the micropart. Figure 4-1 shows an example of

pushing-based manipulation, where the orientation of a micropart is finely adjusted in

one direction. The probe tip is connected to a robotic manipulator through a set of

flexible beams. The snap-lock mechanical joint provides a temporary connection between

the mating features. Through pushing-based manipulation, the orientation of the

micropart can be accurately adjusted.

Figure 4-1 Finely adjust orientation of micropart


An inevitable issue in micromanipulation is the dominance of stiction forces. In pick-

and-place manipulation, microparts are either fixed onto a MEMS chip through a set of

tethers, or joined to other microparts using micro-fasteners. In these cases, mechanical

connections between the microparts are dominant, rather than the stiction forces. But in

pushing-based manipulation, stiction forces must be considered. The main sources of

stiction forces are electrostatic forces, van der Waals forces, and surface tension forces

[46]. Reducing the humidity of the environment can effectively control the surface

tension forces between the probe tip and the micropart. The electrostatic forces and van

der Waals forces between the probe tip and the micropart are served as pulling forces,

which allow the micro-probe pulling the micropart backwards. Compared with the

stiction forces between the probe tip and the micropart, the surface tension of the

adhesive droplets between the mating microparts is dominant. In order to adjust the

orientation of the micropart, the pushing force must overcome the torque generated by the

surface tension of the adhesive droplets. As shown in figure 4-1, the centre of the snap-

lock joint is denoted as O , and the contact point between the probe tip and the micropart

is denoted as 'O . The driving toque yM exerted by the pushing probe is written as

FhM y ×θ×= )sin(

where θ is the tilted angle of the joined micropart, h is the height of the micropart, and F

is the pushing force. The torque generated by the surface tension of adhesive droplets is

denoted as 0yM in figure 4-1. In order to adjust the orientation of the joined micropart,

the exerted torque must fulfill the following condition

0yy MM >


To finely adjust the positions and orientations of the microparts during the pushing-

based manipulation, a vision-based approach is employed to determine the orientations

and positions of the manipulated microparts. For example, to assemble a micropart as

shown in figure 4-1, the orientation of the micropart is obtained from a vision-based

approach. The inclination angle around the y-axis may be determined using the position

of the slot centre, the top edge centre, and the dimension of the micropart. A pattern

matching method [54] is employed to determine the coordinates of the slot centre. After

that, the microscope focuses on the top edge of the micropart. The edge is extracted

through the use of edge detection method. The edge detection method is implemented by

applying a Prewitt filter [54], followed by comparing the filtered image with a threshold.

An optimal threshold is automated calculated using a clustering method [54]. Then the

points on the edge are fitted to a straight line using least-square error method. Figure 4-2

(a) shows a focused top edge of a micropart. The edge information is extracted and

shown in figure 4-2 (b). The top edge of the micropart is fitted to a straight line. The

middle point of the straight line represents the top edge centre of the micropart. The

inclination angle of the micropart θ is determined from

lxx tO /)()cos( −=θ

where tx is the coordinate of the top edge centre in the x-axis direction, Ox is the

coordinate of the slot in the x-axis direction, and l represents the length of the micropart,

which is the distance between the top edge centre and the slot centre.

With the vision-based control, automated hybrid microassembly is possible. The

expected time to automatically assemble a micropart using hybrid microassembly is

within one minute.


Figure 4-2 Top edge detection using computer vision

4.2 Microassembly of three-dimensional rotary mirror

To validate the feasibility of the hybrid microassembly strategy, a three-dimensional

rotary MEMS mirror is assembled. Three-dimensional rotary MEMS mirrors are

fundamental components to build 1×N or N×M optical switching systems. An assembled

1×N rotary MEMS mirror consists of two microparts: a rotary micro-motor and a micro-

mirror. Both of the two microparts are fabricated with PolyMUMPs, a surface

micromachining process [61]. Adhesive mechanical fastener and hybrid microassembly

strategy are employed to assemble the three-dimensional rotary MEMS mirror.

4.2.1 Architecture of three-dimensional rotary MEMS mirror

Optical switches are central components in fiber-optic communication networks.

They are capable to re-direct a light beam from one optical fiber to another. A

configuration of optical switch is to re-direct a light beam from one input port to N output

ports, or in reverse direction, which is referred as a 1×N optical switch. It can be used

either in a 1×N fiber-optic network, or as an element to construct a large-scale N×M

optical switching system. A schematic diagram of a large-scale N×M optical switching

system is shown in figure 4-3. The large-scale N×M optical switching system has N input

nodes and M output nodes. The elements of the input nodes are 1×M optical switches. An


input node re-directs its input light beam to one of the M output optical fibers. Each of

the output optical fibers in the input node connects to one of the output node. An output

node is a 1×N optical switch, which can redirect the light beam from any input optical

fibers to its output port. The input nodes and output nodes are connected together through

optical fibers, the 1×N and 1×M optical switches can be fabricated on different devices

and controlled separately, which makes it possible to achieve large scale. Hence, a high-

performance 1×N optical switch is the key component in the fiber-optic networks.

Figure 4-3 An N×M optical switch constructed with 1×N and 1×M optical switches

Different architectures have been reported to implement 1×N optical switches. A

cascade of 2-D 1×2 optical MEMS switches were used to achieve a 1×8 optical switch in

[55]. The micro-mirrors used in each individual 1×2 optical switch were working in ON

or OFF status to reflect or bypass the light beams. One problem for this type of 1×N


optical switch is that the light beam does not encounter the same number of reflections on

micro-mirrors, which leads to different coupling losses on different light paths. Another

issue is that the coupling loss significantly increases as the number of the cascaded

optical switches becomes very large.

Another configuration of 1×N optical switch is to place N aligned micro-mirrors in a

straight line [56]. Each micro-mirror worked in either the ON or OFF position to reflect

or bypass the light beam, which can re-direct the input light beam to one of the output

ports. In this configuration, the light beam only reflected once on the micro-mirror

regardless of the number of output ports. However, the length of light path would vary

when the light beam was re-directed to different output ports, which would lead to a non-

uniform coupling loss across the output ports.

Another architecture of 1×N optical switch is to use a rotary micro-mirror to re-direct

the light beam to different output ports. Yassen et al. developed a 1×8 optical switch

using a micro-mirror assembled on top of an electrostatic micro-motor [57]. Digital

control was used to steer the input light to different directions. But the assembled mirror

was perpendicular to the top surface of the motor, which led to significant variations of

the coupling loss when the mirror turned a large angle. Another two rotary micro-mirrors

were reported in [58, 59], which used analog control to rotate the micro-mirrors by

deflecting flexible structures. The rotation angle of the micro-mirror was not large

enough, which led to limited scalability. In [58, 59], the micro-mirrors were also

perpendicularly mounted on top of the surfaces of the motors. When the motors rotate,

coupling losses on different output ports would be non-uniform. To achieve uniform

coupling loss across all the output ports, a rotary 1×N optical switch based on a tilt


micro-mirror was developed in [60]. The micro-mirror was assembled onto a rotary

motor with the use of two extra support plates. The micro-mirror was in a 45o position

with respect to the surface of the motor, which guaranteed constant coupling loss across

all the output ports. The micro-mirror was able to turn a full rotation through the use of

digital control. However, assembly of the tilt micro-mirror required two extra supporting

plates, which added complexity and cost to the rotary optical switch.

In this section, hybrid micromanipulation strategy and adhesive mechanical fastener

are employed to assemble a novel three-dimensional 1×N rotary MEMS mirror. A

schematic diagram of the 1×N rotary MEMS mirror is shown in figure 4-4. The rotary

mirror consists of one input port, N output ports, and a rotary micro-mirror. The axial

direction of the input port is perpendicular to the top surface of the rotary motor. The N

output ports lie in a plane parallel to the top surface of the rotary motor. The micro-mirror

is mounted on top of the rotary motor, and in an orientation of 45o with respect to the top

surface of the rotary motor. The axes of the input port and output ports intersect at a point

on the surface of the micro-mirror. The rotary micro-mirror is capable to rotate and re-

direct the incident light beam from the input port to any of the output ports. The 1×N

rotary optical switch can work either in the mode of one input and N outputs, or in the

mode of N inputs and one output. To avoid confusion, we denote the one port

perpendicular to the rotary motor as the input port, and label the N ports parallel to the

rotary motor as the output ports. In practice, the roles of the input port and output ports

are interchangeable.

To obtain constant coupling loss across all the output ports, the output ports are

symmetrically deployed about the axis of the input port. Therefore, the optical path


lengths from the input port to each output port are the same. Another important factor that

affects the coupling loss is the incident angle. In this rotary optical switch, since the

micro-mirror rotates around the axis of the input port, the incident angle maintains at a

constant of 45o. In addition, all the output ports employ identical optical coupling lenses.

Hence, the total coupling loss is almost identical for all the output ports.

Figure 4-4 Schematic diagram of a 1×N rotary optical switch

4.2.2 Microparts design for rotary MEMS mirror

Rotary micro-motor

The 1×N rotary MEMS mirror is assembled from two micro-parts: a micro-mirror and

rotary motor. Both of the micro-parts are fabricated with surface micromachining process,

PolyMUMPs. The purpose of the rotary motor is to rotate the micro-mirror by a precise


angle, so that the light beam is re-directed to a designated output port. The electrostatic

motor is utilized in this design as a precise actuator. The electrostatic actuators are

suitable for use in rotary optical switch because of low power consumption and ease of

control. The rotor of the micro-motor has a diameter of 760 μm and 180 poles. The stator

of the micro-motor has 240 poles. The pole ratio of stator-to-rotor is 4:3. The resolution

of such a step motor is 720 steps per full rotation. Hence, each step represents a rotation

of 0.5o. The controller for this rotary motor is a four-channel pulse generator. To rotate

the motor by a specific angle, a series of pulses are sequentially sent to the four channels.

For a rotation of M steps, the number of required driving pulses is 4M. To create a rotary

micro-mirror with high aspect ratio out-of-plane features, the micro-mirror is

manipulated with a microassembly workstation and assembled onto the rotary motor. In

this microassembly task, the micro-mirror must be manipulated with multiple degrees of

freedom, as well as joined to the micro-motor with an accurate orientation. Hence, the

hybrid manipulation strategy is a suitable approach to assemble this device.

Adhesive mechanical fastener

The adhesive mechanical fastener is employed to assemble the rotary micro-mirror.

As shown in figure 4-5, the adhesive mechanical fastener utilizes both snap-lock

mechanism and adhesive bonding to join the micro-mirror onto the micro-motor. The

mechanical snap-lock mechanism provides a temporary joint, which allows for further

adjustment of the orientation of the assembled micro-mirror. In addition, the snap-lock

mechanism has the capability to self-align the mating features. The adhesive bonding,

which connects the micro-mirror to the rotary motor through two adhesive droplets,

creates a strong permanent connection between the two microparts.


Figure 4-5 An adhesive mechanical fastener for rotary MEMS mirror

The snap-lock joint mechanism design has been well studied in [3]. Hence, this work

leverages the design in [3] to temporarily join the micro-mirror. In order to position the

micro-mirror in an orientation of 45o with respect to the rotary motor, necessary

modifications are made in the snap-lock joint design. As shown in figure 4-5, a slot is

made in a base structure on the rotary motor. Two tips are connected to the body of

micro-mirror through two flexible beams. The two beams deflect inwards as the tips are

inserted into the slot. Forces between the tips and the slot, generated by the elastic

deflection of the two flexible beams, keep the assembled micropart positioned in the slot.

The snap-lock joint feature also provides self-alignment ability between the mating

features along the long axis direction of the slot.


In order to assemble the micro-mirror in a position of 45o with respect to the top

surface of the rotary motor, the width of the slot sw should fulfill the following

requirement

sms tww +≥ 2 (4-1)

where mw is the thickness of the micro-mirror, and st is the thickness of the base

structure, as shown in figure 4-6. In this work, the tips and the flexible beams of the

micro-mirror are fabricated using the Poly1 layer in PolyMUMPs. The thickness of

micro-mirror mw is 2 μm. The base structure is fabricated with the Poly2 layer in

PolyMUMPs. The thickness of the base structure st is 1.5 μm. The width of the slot sw

should be larger than 4.3 μm. Considering the fabrication errors, the width of the slot sw

is set to 5 μm, which allows for adjustment of the orientation of the assembled micro-

mirror using pushing-based micromanipulation.

Figure 4-6 Side view of an assembled micro-mirror

4.2.3 Hybrid microassembly procedures

In this work, the hybrid micromanipulation strategy, which includes pick-and-place

and pushing-based manipulations, is utilized to manipulate the micro-mirror. The pick-


and-place manipulation has the capability to globally manipulate the micro-mirror with

multiple degrees of freedom. The pushing-based manipulation can achieve high

positioning accuracy. The process to assemble a micro-mirror using the hybrid

manipulation strategy consists of the following steps:

(1) Depositing adhesive droplets to target locations.

(2) Joining the micro-mirror using the pick-and-place manipulation.

(3) Pushing the assembled micro-mirror to finely adjust its orientation.

(4) Curing the adhesive to create a strong mechanical connection.

A square deposit tip with an edge length of 20 μm is utilized to deposit adhesive

droplets onto their target spots. Figure 4-7 (a) shows the deposit tip dipped into the

adhesive reservoir by several microns, so that enough adhesive adheres to the deposit tip.

Because of the surface tension, the adhesive does not adhere to the thin beam. In this way,

the sizes of adhesive droplets are controlled by the size of the deposit tip. Figure 4-7 (b)

shows the operation to deposit adhesive droplets onto the two target spots on the micro-

motor. The areas of the deposited adhesive droplets are about 20×20 μm. A problem in

the design of the micro-motor is that the two adhesive target spots are too close to the slot,

which increases the complexity in the following assembly operations. This problem can

be resolved by placing the adhesive target spots further away from the slot in the snap-

lock interface features.


Figure 4-7 Micromanipulation of adhesive droplets for micro-mirror assembly

The micro-mirror is a rectangular plate with dimension of 247×174 μm. To increase

the reflectivity, a layer of gold is deposited onto the surface of the micro-mirror. A

passive microgripper and snap-lock joint, developed by Dechev et al. [3], are employed

to manipulate the micro-mirror. Grasping features and snap-lock features are developed

on the micro-mirror and the micro-motor, and fabricated with PolyMUMPs process.

In order to assemble the micro-mirror onto the micro-motor, global manipulation of

the micro-mirror using pick-and-place strategy is first carried out. The basic procedures

to manipulate the micro-mirror using pick-and-place manipulation are

(1) grasping a micro-mirror with a microgripper

(2) translating and rotating the micro-mirror to desired position and orientation

(3) joining the micro-mirror to the rotary motor

(4) releasing the micro-mirror from the microgripper.

Here, the pick-and-place manipulation of the micro-mirror is carried out under an optical

microscope operated in a tele-operation manner. Vision-based automatic manipulation of

the micro-parts using pick-and-place strategy is presented in next chapter.

Figure 4-8 shows the process to assemble the micro-mirror under an optical

microscope using pick-and-place strategy. In figure 4-8 (a)-(c), a passive microgripper


grasps the micro-mirror, then breaks the tethers, and finally removes the micro-mirror

from the MEMS chip. The next step is to rotate the grasped micro-mirror by 90o, and

translate it towards the target slot on the micro-motor. Because it would be difficult to

visualize the fully vertical micro-mirror, the micro-mirror is rotated by 100o in the

experiments. Figure 4-8 (d) shows the re-oriented micro-mirror, where the microscope

focuses on the snap-lock tips of the micro-mirror. A rectangle is drawn on the image to

enclose the snap-lock tips and label its position. Then, the microscope focuses on to the

surface of the micro-motor, and the snap-lock slot is aligned with the rectangle in the

image plan. Figure 4-8 (e) and (f) show the positions of the snap-lock slot before and

after alignment with the rectangle. The following step is to join the tips into the slot and

release the micro-mirror from the microgripper. Figure 4-8 (g) and (h) show the

procedures to join and release the micro-mirror.


Figure 4-8 Sequential microscopic images in pick-and-place a micro-mirror

For pick-and-place manipulation, it is more difficult to join the micro-mirror to the

micro-motor with an orientation of 45o than the orientation of 90 o. On the other hand, the

released micro-mirror might deviate from its ideal position, due to some unpredictable

forces, such as vibration, electrostatic forces, van der Waal forces, and surface tension.

To increase the accuracy of microassembly, a pushing-based manipulation is carried out

following the pick-and-place manipulation to finely adjust the orientation of the micro-

mirror.

As shown in figure 4-9, the point s is the slot center of the rotary motor, the point t is

the top edge center of the micro-mirror, and the point t’ is the project of point t on the top

surface plane of the rotary motor. The parameter l, which is the distance from point t to


the point s, is determined from the layout of MEMS chip. The angle between the micro-

mirror and the rotary motor θ is determined from

klyyxx stst

22 )()()cos(

−+−=θ (4-2)

The parameter k is a coefficient that converts microns to pixels. The points s and t’

are moving during the pushing-based manipulation. The coordinates of points s and t’ are

determined from computer vision and linear encoders.

Figure 4-9 Orientation of assembled micro-mirror

At the beginning of the pushing-based manipulation, the microscope focuses on the

surface of the rotary motor. The initial coordinates of the point s ),( 00 ss yx are determined


using pattern matching. In this work, the pattern matching is implemented with the

function of “IMAQ Match Pattern 2” in the LabVIEW and the NI Vision Development

Module (NI VDM version 8.2). The slot on the rotary motor is located on the MEMS

chip, which is moving together with the platform of the microassembly robot. Linear

encoders on the microassembly robot are employed to measure the displacements of the

slot with respect to its initial position. In this work, the resolution of the linear encoder is

0.1 μm. During the pushing-based manipulation, the coordinates of the point s ),( ss yx

could be determined from its initial position and the linear encoders.

)( 00 eess xxkxx −+= , )( 00 eess yykyy −+= (4-3)

where ex and ey are the encoder positions at the current time; 0ex and 0ey are the

encoder positions at the beginning of the pushing-based manipulation; k converts the

encoder positions from microns to pixels.

The coordinates of the point t’ ),( tt yx are determined from computer vision in real

time. The microscope first focuses on the top edge of the micro-mirror. The top edge is

extracted by employing an edge-detection function. The function of “IMAQ

EdgeDetection” in NI VDM is utilized to detect the top edge, where the edge-detection

method is selected as “Prewitt”, the parameter of threshold is automatically computed

using “IMAQ AutoBThreshold” function with the method of clustering. The points on

the extracted edge are fitted to a straight line using a least-square error method. The fit-

line function in NI VDM is “IMAQ Fit Line”. The middle point of the fitted line

represents the position of point t and t’.


When the micro-mirror rotates around the slot, the top-edge of the micro-mirror may

move out of focus. Let st xxx −=Δ and st yyy −=Δ . The distance from the point t to the

point t’ is determined from

2222' yxlkdtt Δ−Δ−= (4-4)

Because the positions of the point s and point t are determined in real time, the

microscope can adjust its focal plan to maintain the top edge of the micro-mirror in focus.

Therefore, as long as the pushing-based manipulation are carried out in small steps, the

top edge of the micro-mirror will be always in focus, which ensures that the coordinates

of the point t’ ),( tt yx are determined from computer vision in real time. From equation 4-

2, the angle between the micro-mirror and the rotary motor θ is determined in real time.

In this work, the pushing-based manipulation is carried out in tele-operated manner.

The real-time measurement of angle θ provides an effective assistance to the operator.

The real-time measurement of angle θ can be also used in automated pushing-based

manipulation. The length of the micro-mirror l is 400 μm. The coefficient k that converts

microns to pixels is 0.36 μm/pixel. The target orientation of the micro-mirror is 45o.

From equation 4-2, the target distance from point s to point t’ is

pixelsklyyxx stst 786)cos()()( 22 ==−+− θ

Firstly, the microscope focuses on the surface of the rotary motor. The initial

coordinates of the point s ),( 00 ss yx are determined as (834, 340). During the pushing-

based manipulation, the coordinates of the point s ),( ss yx are determined from equation

4-3. At the same time, the top edge of the micro-mirror is extracted from computer vision.

The displacements of the point s and the point t’ are plotted in figure 4-10. The

corresponding angles of the micro-mirror are shown in figure 4-11. The final coordinates


of the point s are (1081, 340). The final coordinates of the point t’ are (294.5, 323.5). The

angle of the micro-mirror is 44.91±0.03o.

During the pushing-based manipulation, the rotor of the micro-motor could rotate

around its shaft, which would make it difficult to achieve accurate assembly. A

temporary fixture that is used to prevent the rotation of the micro-motor would be helpful

in the microassembly of the micro-mirror.

Figure 4-10 Displacement of slot and mirror top edge during pushing


Figure 4-11 Inclination angle of micro-mirror plate during pushing

After the micro-mirror is pushed to its target orientation, UV-light is applied to curing

the adhesive droplet. A strong, permanent mechanical connection is created to join the

micro-mirror onto the rotor of the micro-motor. Figure 4-12 shows the scanning electron

microscope picture of an assembled 45o rotary micro-mirror.


Figure 4-12 Assembled rotary MEMS mirror

57

Chapter 5

Vision-Based Automated Microassembly

This chapter presents a vision-based automated micromanipulation methodology used

to assemble micro-parts with pick-and-place strategy. Sequential microassembly sub-

tasks are carried out under a high-magnification optical microscope. Vision-based

feedback control is used for accurate positioning microparts in three-dimensional space

during microassembly tasks. To address the issue of low depth of field in high-

magnification optical microscope, special alignment strategies are utilized to perform the

micro-grasping and micro-joining tasks. A novel vision-based contact sensor is

developed to facilitate the high-accuracy micro-joining tasks. The necessary steps

towards fully automated microassembly of complex three-dimensional MEMS devices,

i.e., grasping a micropart, manipulating it, joining it to another micropart, and finally

releasing it from the microgripper, have been successfully carried out using a robotic

micromanipulator. Experiments demonstrate the efficiency of the automated

microassembly approach.

5.1 Procedures of automated pick-and-place microassembly

Assembly of a micropart using pick-and-place manipulation strategy consists of the

following sequential sub-steps: grasping a micropart, manipulating it to a designated

position and orientation, joining it to another micropart, and releasing it from the

microgripper. Figure 5-1 describes the procedures of an automated pick-and-place

microassembly tasks, which consists of the following five steps:

Step 1. Preparation:

Chapter 5 Vision-Based Automated Microassembly 58

Before the automated microassembly task starts, the operator must first designate

both a micropart for assembly and its target slot, and upload the patterns of the

microgripper, micropart and the slot to the vision processing software. As shown

in Figure 5-1 (a), the microgripper used to grasp a micro-part must be manually

bonded to a probe attached to the micromanipulator. The microgripper is initially

placed at a higher z-axis position than the MEMS chip substrate, and manually

aligned with a corner of the MEMS chip in the x and y-axis directions. The CAD

model of the MEMS chip is loaded to the automated microassembly program, so

that the designated micropart and its target base structure can be brought into the

field of view of the microscope by using open-loop control.

Step 2. Grasping a micropart:

A micropart is fixed on the MEMS chip through a set of tethers. A three-stage

alignment strategy, discussed in detail in the next section, is proposed to grasp the

fixed micropart based on a coarse-to-fine approach. In the proposed three-stage

alignment strategy, the jaws of microgripper and the plug of the micropart are first

aligned in the x and y-axis directions using a coarse vision-based feedback control,

then aligned in the z-axis direction, finally accurately aligned in the x and y-axis

directions using another fine vision-based feedback control. When the

microgripper fully grasps the micropart, shown in figure 5-1 (b), the microgripper

maintains a force against the micropart in x-axis direction to separate the micro-

part from the substrate by breaking the tethers.

Step 3. Manipulating a grasped micropart through three-dimensional space:


As shown in figure 5-1 (c), the grasped micropart is rotated by 90 degrees to a

vertical orientation with respect to the slot and translated to a position above the

designated slot. This step is carried out in an open loop manner. Since the position

of the target base structure can be obtained from the CAD information of the

MEMS chip, the designated base structure may be directly brought into field of

view of the microscope using open loop control.

Step 4. Joining a micropart to another micropart:

This joining task is carried out in two sub-steps. First, the coordinates of the tips

of the manipulated micropart are determined in three-dimensional space using a

vision-based method, which is discussed in detail in section 5.4. The next sub-step

joins the micropart using a two-stage alignment: the tips and the slot are first

aligned in x and y-axis directions, then aligned in z-axis direction. In the

alignment in the z-axis direction, the contact status between the tips and the slot is

determined with a vision-based contact sensor.

Step 5. Releasing a micropart:

After the micropart is joined to the base structure, the substrate, together with the

base structure and joined micropart, is translated away from the microgripper in

the negative z-axis direction. The two jaws of the microgripper will open up to

release the micropart.


Figure 5-1 Procedures of automated pick-and-place microassembly

5.2 Three-stage automated micrograsping strategy

A passive microgripper, develop by Dechev et al. [3], is used in this work to grasp

microparts. Here, a brief overview of the passive microgripper and micropart is provided.

The detailed description of the microstructures is presented in [3]. As shown in figure 5-2,

the passive microgripper consists of two jaws, two sets of compliant beams, and a

bonding pad. The bonding pad is used to bond the microgripper to the free end of the

probe in the microassembly robot. Each jaw is connected to the bonding pad through

three compliant beams. The mating feature in the micropart that can be grasped by the

microgripper is referred as a plug. The micropart is tethered to the substrate. When the

micropart is commanded to insert the plug into the two jaws of the microgripper, the two


jaws deflect outwards. After the two jaws fully grasp the plug, the micropart continues to

maintain a force against the microgripper, ultimately leading to the release of the

micropart by breaking the two tethers. Two guides, which are fixed on the substrate 2 μm

away from the edge of the micropart, are employed to prevent the rotation of the

micropart. The objective of a micrograsping task is to accurately align the plug of the

micropart with the two jaws of the microgripper in three-dimensional space, and remove

the micropart from the substrate.

Figure 5-2 Passive microgripper and micropart

To automatically grasp a micropart in three-dimensional space with high accuracy, a

three-stage automatic micrograsping strategy based on vision-based control is proposed.

A flow chart of the three-stage automated micrograsping strategy is shown in figure 5-3.

Before the automated grasping, four preparation tasks are carried out manually: (i)


calibrating the rotation matrix R; (ii) bonding a passive microgripper to the

microassembly robot; (iii) selecting the patterns of the micropart and microgripper; and

(iv) initially align the microgripper with the MEMS chip. To determine the positions of

the microgripper and the micropart, three patterns are chosen, as shown in figure 5-2,

which include the upper and lower jaws of the microgripper, and a portion of the

micropart. Prior to automated grasping, the microgripper is manually aligned with the

MEMS chip. Because the layout information of the MEMS chips is known in the design

phase, the micropart is directly brought into the field of view of the microscopy using

open-loop control. Note that all manual tasks only need to be performed once for

repetitive micrograsping tasks. The remaining blocks of the flow chart in figure 5-3

represent the tasks that are performed automatically.

Figure 5-3 Flow chart of automated micrograsping in three-dimensional space

The objective of Stage I is to coarsely align the microgripper with the designated

micropart in the x and y-axis directions, as shown in figure 5-2. At the beginning of this

stage, designated micropart is brought into the field of view of the microscope using the

CAD model of the MEMS chip and open loop control. Then the microscope translates in

the z-axis direction to focus on the microgripper by searching for the peak of the image


focus values. The geometric center position of the upper-jaw and the lower-jaw patterns

are determined using a pattern matching function. The patterns of the upper-jaw and the

lower-jaw are non-deformable and roughly symmetric with respect to the center axis of

the microgripper that is parallel with the x-axis, as shown in figure 5-2. Then, the

microscope translates along the z-axis direction to automatically focus on the surface of

the substrate. The geometric center position of the micropart pattern is determined using a

pattern matching function. A coarse vision-based feedback controller is employed to

align the micropart with the microgripper in the x and y-axis directions. The coarse

vision-based feedback controller is addressed in the next section. When the coarse

alignment is completed, the micropart and microgripper are aligned in the y-axis direction,

and maintain a distance Tl in the x-axis direction. As shown in figure 5-2, the micropart

has a plug and two alignment plates. The alignment plates are longer than the plug by 6

μm. The distance Tl is selected to ensure that the front edges of the gripper jaws just pass

the front edges of the alignment plates, but do not exceed the front edge of the plug. Such

that the jaws of the microgripper overlap on part of the alignment plates, but do not

interfere with the plug. Note that figure 5-2 only shows the relative position in the x-y

plane between the microgripper and micropart. At the end of Stage I, the microgripper

and micropart have not been aligned in the z-axis direction.

The objective of Stage II is to align the microgripper with the micropart in the z-axis

direction. In Stage I, the microgripper has sequentially focused on the microgripper and

the micropart. The distance from the microgripper to the micropart in the z-axis direction

is determined by calculating the z-axis travel distance of the microscope from the position

where the microscope focuses on the microgripper to the position where the microscope


focuses on the micropart. Hence, in Stage II, the micropart is translated in the negative z-

axis direction using open-loop control, to the horizontal plane where the microgripper lies

in. Due to the errors in vision-based auto-focus and open-loop control, the micropart and

microgripper may not be accurately aligned in the z-axis direction. To achieve high

accuracy in the z-axis alignment, the micropart keeps pushing against the microgripper in

the negative z-axis direction by several microns. Figure 5-4 shows the side-view when the

micropart is pushed against the microgripper. In stage I, the jaws of the microgripper

have been placed on top of the two alignment plates. Because the jaws are connected to

the bonding pad through two sets of compliant beams, when the jaws of the microgripper

contact with the alignment plates of the micropart, the compliant beams will deflect, such

that the microgripper and the micropart are perfectly aligned in the z-axis direction. Note

that, to ensure that the front edges of the jaws always contact with the alignment plates,

the microgripper has a small inclination angle with respect to the micropart, which is

experimentally determined. In this work, the inclination is set to 5 degrees. At the end of

Stage II, the micropart is ready to be grasped by the microgripper.

Figure 5-4 Side view of alignment in the z-axis direction

The objective of Stage III is to finely align the microgripper with the micropart in the

x and y-axis directions, until the micropart is completely grasped by the microgripper. In


each control iteration, the geometry centre positions of the upper-jaw pattern and the

lower-jaw pattern, and the geometry centre position of the micropart pattern are

determined using a pattern matching function. The micropart is translated in the x-axis

direction towards the microgripper in small steps. In this process, the two jaws of the

microgripper deflect outwards. A vision-based feedback controller is employed to

maintain accurate alignment of the micropart with the microgripper in the y-axis direction.

The objective of this controller is to ensure an accurate alignment of the micropart with

the microgripper in the y-axis direction by maintaining symmetric displacements on the

two jaws of the microgripper.

After the microgripper fully grasps the micropart, the micropart continues translating

towards the microgripper in the positive x-axis direction, ultimately leading to the

removal of the micropart from the substrate by breaking the two tethers. Two guides,

which are fixed on the substrate, are employed to prevent the rotation of the micropart in

the x-y plane during the process of breaking the two tethers. The tethers and guides,

designed by Dechev et. al. [3], ensure that the micropart can be removed from the

substrate in a efficient and reliable manner. Manual removal of the micropart using the

tethers and guides has been successfully validated in [3]. In this work, the automated

removal of the micropart from the substrate is carried out in the same way as that in the

manual removal of the micropart.

5.3 Coarse-to-fine vision-based control

Two vision-based feedback controllers are developed to align the micropart with the

microgripper in the x and y-axis directions, in a coarse-to-fine approach. During this

process, the microgripper remains at a fixed position, while the micropart translates


towards the microgripper. The patterns used in the two vision-based feedback controllers

are selected as shown in figure 5-2, with the center coordinates of the micropart, upper-

jaw, and lower-jaw patterns denoted as (xp, yp), (xuj, yuj), and (xlj, ylj), respectively. To

simplify the expression, the centre coordinates of the upper and lower jaws are denoted as

jx and jy , where

)(21

ljujj xxx += , )(21

ljujj yyy += (5-1)

In the coarse alignment in Stage I, the target position of the micropart is ( cx , cy ),

where

Tjc lxx −= )0( , )0(jc yy = (5-2)

where )0(jx and )0(jy are the initial centre coordinates of the two jaws obtained from the

pattern matching, and remain constants during the entire process of the coarse alignment.

The output signal of the coarse alignment feedback controller is written as

⎥⎦

⎤⎢⎣

⎡−

+−−=⎥

⎦

⎤⎢⎣

⎡−−

−=⎥⎦

⎤⎢⎣

⎡)0()(

)0()()()(

)()(

jp

Tjpc

cp

cpc

y

x

ykylxkx

kykyxkx

kkuku

RR (5-3)

where ck is a proportional gain, Tyx kuku ])()([ are the output signals to the

microassembly robot in the x and y-axes at the kth control iteration loop, R is the

rotational matrix introduced in Chapter 2. In equation 5-3, the parameters of )(kx p , )(ky p ,

)0(jx , and )0(jy are determined from pattern matching, and the parameter of Tl is

determined from the geometry of the micropart.

Following the coarse alignment, another fine alignment vision-based feedback

controller is employed in Stage III. At each control iteration loop, the micropart is

translated in the x-axis direction towards the microgripper in small steps. During this


operation, the two jaws of the microgripper deflect outwards. The objective of this fine

alignment controller is to finely align the micropart with the microgripper in the y-axis

direction by ensuring that the two jaw deflections are symmetric about the center axis of

the microgripper. The output signal of the fine alignment controller is written as

)]}0()([)]0()([2)( 2221 jjjjpy ykyxkxkkv −+−−= R{R (5-4)

where kp is a proportional gain, vy(k) is the motion command sent to the y-axis stepper

motor at the kth control iteration loop, )(kx j and )(ky j are the centre point coordinates of

the two jaws at the kth control iteration loop, )0(jx and )0(jy are the initial centre point

coordinates of the two jaws before the two jaws deflect outwards, and 21R and 22R are

the elements of the rotation matrix R . Note that the y-axis motion command is

determined by the relative displacements of the two jaws with respect to their own

original positions recorded at the beginning of Stage III, rather than the relative

displacement between two different patterns respectively located on the microgripper and

the micropart. The control strategy, as expressed in equation 5-4, ensures

0)]0()([)]0()([ 2221 =−+− jjjj ykyxkx RR (5-5)

21R and 22R convert the deflections of the two jaws in the image coordinates into the

deflections in the y-axis direction in the robot coordinates. Hence, the fine alignment

vision-based feedback controller ensures that the two jaws symmetrically deflect about

the center axis of the microgripper in the y-axis direction in the robot coordinates.

The achievable accuracies of the vision-based feedback controllers are affected by

three factors: (i) the pattern-selection errors, i.e., the selected patterns may deviate from

their ideal positions; (ii) the errors from pattern-matching algorithm, i.e., with an ideal

pattern, the pattern-matching results still differ from one pattern matching from another;


(iii) the accuracy of parameter Tl relies on the dimensional accuracy of the MEMS chip,

and might vary amongst different microparts. Note that these errors (i) are system errors,

which remain constant during the process of vision-based feedback control. In contrast,

the errors (ii) arise from the pattern-matching algorithm, which may differ from one

pattern-matching process to another. Here, we only discuss the method to reduce the

system errors (i) and dimensional errors (iii). Improving the accuracy of the pattern-

matching algorithm is not discussed in this paper.

One advantage of the fine alignment controller is the capability to eliminate the

pattern-selection errors. Due to the pattern-selection errors, the pattern of the two jaws

may deviate from their ideal positions. Let the pattern-selection errors of the upper and

lower jaws in the x and y-axis directions be ujex , ujey , ljex and ljey . To simplify these

expressions, the pattern-selection errors of the centre point of the two jaws are denoted as

jex and jey , where

)(21

ljujj exexex += , )(21

ljujj eyeyey +=

The output signal of the fine alignment vision-based feedback controller due to these

pattern-selection errors becomes

)]}0()([)]0()([2

]})0()([])0()([2)('

2221

2221

jjjjp

jjjjjJjjpy

ykyxkxk

eyyeykyexxexkxkkv

−+−−=

−−++−−+−=

R{R

R{R (5-6)

Comparing equation 5-4 with equation 5-6, we have )()(' kvkv yy = . Hence, the accuracy

of the fine alignment is not affected by the errors introduced through pattern selections.

However, the accuracy of coarse alignment in the y-axis direction is affected by the

pattern-selection errors. From equation 5-3, the coarse alignment vision-based feedback

controller in the y-axis direction is


)]}0()([])0()([)( 2221 jpTjpcy ykylxkxkku −++−−= R{R (5-7)

Denote the pattern-selection errors for the micropart as pex and pey , and denote the error

in the dimension of MEMS chip as Tel . Then, the output signal of the coarse alignment

controller in the y-axis direction, with considering the pattern-selection errors, becomes

]})0()([])0()([)(' 2221 jjppTTjjppcy eyyeykyellexxexkxkku −−++++−−+−= R{R (5-8)

Since the errors are not predictable, we have yy uu ≠' .

Comparing equation 5-6 with equation 5-8, the fine alignment controller is not

affected by the pattern-selection errors and dimension errors of the MEMS chip, which

leads to an accurate alignment in the automatic micrograsping.

Experiments were conducted to examine the performance of the automated

micrograsping method. The distance Tl is measured: Tl =157μm. A passive microgripper

is bonded to the probe tip of the microassembly robot. The bonded microgripper has an

inclination angle of 5o with respect to the MEMS chip. The microgripper and MEMS

chip are initially aligned. After these manual preparations, fully automatic three-

dimensional automatic micrograsping tasks were conducted.

5.4 Experiments on automated micro-grasping

Figure 5-5 illustrates the process of the automated three-dimensional micrograsping.

At the beginning of the micrograsping task, the micropart is brought into the field of view

of the microscope using the layout of the MEMS chip and open-loop control. Both the

microgripper and the micropart are out of focus, as shown in Figure 5-5 (a). In Stage I,

the microscope first automatically focuses on the microgripper, and the pattern

coordinates of the two jaws are determined. The focused microgripper is shown in Figure

5-5 (b). Then the microscope focuses on the micropart, as shown in Figure 5-5 (c), and


subsequently the micropart and microgripper are aligned in the x and y-axis directions by

using the coarse vision-based feedback controller. Figure 5-5 (d) shows the aligned

microgripper and micropart at the end of Stage I. Note that when performing the coarse

alignment, the microgripper and the micropart are located at two different positions in the

z-axis direction. This offset in the z-axis direction is determined by recording the travel

distance of the microscope in the z-axis direction between the two focal planes. In Stage

II, the distance between the microgripper and micropart in the z-axis direction is

determined, allowing the micropart and microgripper to be directly aligned with no offset

in the z-axis direction. Compliant beams in microgripper and two alignment plates in the

micropart are utilized to ensure an accurate alignment in the z-axis direction. The result is

shown in figure 5-5 (e). Finally, in Stage III, the micropart is displaced in the x-axis

direction towards the microgripper until it is completely grasped. At the same time, the

fine vision-based feedback controller, based-on the position feedback signals of the two

jaws, is employed to finely align the micropart with the microgripper in the y-axis

direction. The fully grasped micropart is shown in figure 5-5 (f). The operation to

automatically grasp a micropart requires 7.9 seconds to complete, as shown in figure 5-5

(a)-(f). This time may vary slightly with different initial relative positions between the

microgripper and the micropart. After completely grasping the micropart, the MEMS

chip substrate, together with the grasped micropart, continues translating towards the

microgripper in the x-axis direction by 20 μm. Figure 5-5 (g) and (h) show process of

breaking the tethers. After the rupture of the first tether, the grasped micropart tends to

rotate. The guide besides the micropart prevents the potential rotation, and leads to

successful rupture of the second tether.


(a) (b)

(c) (d)

(e) (f)


(g) (h)

Figure 5-5 Automated micrograsping procedures: (a) Beginning of micrograsping, (b) Stage I: Auto-focus on the microgripper, (c) Stage I: Auto-focus on the substrate, (d) Stage I: Coarse alignment in the x and y-axis directions, (e) Stage II: Alignment in the z-axis direction, (f) Stage III: Fine alignment in the y-axis directions, (g) translation of micropart towards microgripper in the x-axis direction to break the first tether, and the rotation of the micropart is prevented by the guides, (h) the second tether breaks, and the micropart is removed from the substrate.

In the stage of fine alignment of the micropart with the microgripper, the fine vision-

based feedback controller is employed to ensure the two jaws on the microgripper deflect

the same amount in the y-axis direction. The output signal of the controller is shown in

figure 5-6. The alignment errors are recorded and shown in figure 5-7. The average

alignment error in the whole process is –0.07 μm, with a standard deviation of 0.12 μm.

Without the use of the feedback controller in the fine alignment tasks, the alignment

errors between the microgripper and the micropart in the y-axis direction would increase

significantly. Figure 5-8 shows the deflections of the jaws and the alignment errors in a

fine alignment task, where no feedback control is applied in the y-axis direction. The

average alignment error between the micropart and the microgripper in the y-axis

direction is –0.48 μm, with a standard deviation of 0.17 μm, which is much worse than

the results of using the proposed fine alignment vision-based feedback controller.


Figure 5-6 Output signal of fine alignment controller

Figure 5-7 Jaw deflections and alignment error with fine vision-based control


Figure 5-8 Jaw deflections and alignment error without fine vision-based control

In micrograsping tasks, failures may occur due to many unpredictable factors, such as

vibration disturbances, illumination variations, image processing errors, calibration errors

of the system, or thermal expansion of the microassembly robot. In order to test the

performance of the automated micrograsping methodology, repetitive automatic

micrograsping tasks are carried out. System calibration and pattern learning are

performed once at the beginning of the experiment. Different microgrippers are manually

bonded to the microassembly robot. The grasping attempts are performed 50 times on

different microparts, and 47 out of the 50 grasping attempts succeed, giving a success rate

of the automatic micrograsping of 94%. The reason for the three failed grasping attempts

is that the pattern of micropart cannot be found in vision-based feedback control. The


shadow cast by microparts changes the image seen by the video microscope, leading to

potential failure in pattern matching. Improving the illumination conditions and using a

better pattern-matching algorithm may solve this problem. Significant vibration

disturbances could also lead to failures of the pattern-matching algorithm, because

vibrations shake the camera and lower the imaging quality. A shock-isolation table may

suppress most of the external vibrations, which would improve the success rate of the

automatic micrograsping tasks.

5.5 Two-stage automated micro-joining strategy

The low depth of field in high-magnification optical microscope also complicates the

automated micro-joining tasks in three-dimensional space. When inserting the tips of the

micropart into the slot on the base structure, the locations of the slot and the micropart

tips should be determined before both of these structures appear simultaneously within

the depth of field of microscope. Note that the microscope can only provide clear images

of the mating features when the tips and the slot are positioned simultaneously within the

depth of field of the microscope. To address the problem of low depth of field in high-

magnification microscopy vision system, a two-stage alignment strategy is proposed to

perform the three-dimensional micro-joining tasks, where the mating features are aligned

in two sequential stages. In stage I, the tips of the micropart are aligned with the slot in

the x and y-axis directions, but maintain a certain offset distance in the z-axis. In stage II,

the tips and the slot are aligned in the z-axis direction.

Before the two-stage alignment, the slot is positioned to be coincident with the z-axis,

below the tips. In Stage I, the microscope automated focuses on the tips of the reoriented

micropart. A pattern matching method is employed to determine the position of the tips in


the x and y coordinate direction. In the next step, the position of the slot in the z-axis is

re-adjusted to ensure the shadow of the probe is not cast on the slot. Then the microscope

automated focuses on the surface of the slot. The distance between the tips and the slot in

the z-axis direction is recorded using a linear encoder. With these steps concluded, the

slot is positioned in the microscope focal plane, and its position can be determined in

real-time with the use of a pattern matching method. With the two coordinate locations of

the tips in the x-y plane obtained in the previous step, a position-based feedback control,

is employed to align the tips with the slot in the x and y-axis directions. At the end of

stage I, the tips of the micropart and its target slot are aligned in the x and y-axis

directions, ready for insertion into the slot. In stage II, the microscope is brought into

focus with the tips of the reoriented micropart. The substrate, together with the slot, is

commanded to move in the positive z-axis direction towards the tips, until the two tips

and the slot are completely aligned. In this insertion subtask, the contact status between

the substrate and the tips is detected using a novel vision-based contact sensor.

5.6 Auto-focus on reoriented micropart

Automated focusing on the reoriented micropart is an important step towards fully

automated micro-joining tasks. In order to provide a bright and uniform illumination to

the objects in focal plane, the MEMS chip substrate is placed 400 microns lower than the

focal plane of the microscope in the z-axis direction. The tips of the micropart are initially

located above the focal plane. Then, the microscope and the MEMS chip substrate are

commanded to move in the positive z-axis direction, in one-micron steps. In each step, a

Prewitt filter is applied to the image to extract the outer contours of the features. Each


pixel is assigned the maximum value of its horizontal and vertical gradient obtained with

the following Prewitt convolution kernels:

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡

−−−

=101101101

1P , ⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡ −−−=

111000111

2P

The filtered image highlights the contours in the original image. Figure 5-9 shows the

effect of the Prewitt filter. The left image in figure 5-9 shows the tips of the reoriented

micropart. By applying the Prewitt filter, the contour features of original image are

extracted and shown in the right side of figure 5-9.

Figure 5-9 Contour feature extraction for reoriented micropart

The average pixel value of the filtered image represents the degree of focus, which is

calculated from

∑=

=n

iip

np

1

1ˆ

where the p is the average pixel value, or focus value, n is the number of pixels, ip is the

gray value of ith pixel in the filtered image. The tips of the reoriented micropart are in the


lowest position in the z-axis direction. When the tips of the micropart appear in the field

of view, the focus value of the filtered image increases sharply. The gradient of the focus

value is determined using the following second-order differential filter:

2ˆˆ −−= kkk ppG , ( 2≥k )

where k represents the steps in the z-axis direction, kG is the gradient of the focus value

at the kth step, kp and 2ˆ −kp are the focus values at the k th and (k-2) th steps. Figure 5-10 is

a plot of the second order gradient of the focus value versus the relative position of the

tips in the z-axis direction.

Figure 5-10 Gradient of focus value

When the gradient of the focus value exceeds a pre-defined threshold that is

determined experimentally, the tips are well focused. Because the gradient of the focus

value does not rely on the brightness of the image, the use of gradient of the focus value

to focus on the tips of an reoriented micropart is more robust than the method that

directly utilizing the focus value.


5.7 Contact sensor for three-dimensional micro-joining

When performing the three-dimensional micro-joining tasks, the contact status

between the tips and the slot must be measured within micron or sub-micron accuracy.

Limited by the low depth of field of the optical microscopy system, it is difficult to

directly measure the distance between the tips and the slot in the z-axis direction. In this

work, a vision-based contact sensor is developed to assist in the automated micro-joining

operation. The geometry of the snap-lock joint feature, which is designed to fix the

micropart to the base structure, is shown in figure 5-11. Note that the tips of the micropart

are rounded due to the rounding effect of the micro-fabrication process. The structure of

the joint features consists of two L-shaped flexible beams, two tips, and one slot. The L-

shaped beams of the micropart elastically deflect inwards as the tips are inserted into the

slot.

Figure 5-11 Cross section of snap-lock joint feature


During the process of insertion, the gray level of the sub-image in the area around the

slot varies as the depth of insertion increases. The sub-image in the area around the slot is

shown as a region of interest, enclosed within a rectangle in figure 5-12. At the beginning

of the micro-joining operation, the gray level of the region of interest is relatively low,

because the base structure and the slot are out of focus and their image is blurred. As the

MEMS chip is commanded to move towards the focal plane and hence becomes better

focused, shown in figure 5-12 B and C, the average gray level of the region of interest

increases. When the tips touch the slot, the two flexible beams deflect inwards, and the

tips of the micropart start to close, which increases percentage of the dark area in the

region of interest. Hence, the average gray level in the region of interest starts to decrease

after contact occurs, shown in figure 5-12 D. An average gray level curve of the region of

interest in the entire insertion process is shown in figure 5-13, where one step represents

an insertion depth of one micron, and the amplitude represents the average gray level of

the region of interest in the image. The gradient of the gray level changes from positive to

negative when the tips of the micropart touch the slot on the base structure. The

maximum gray level occurs at the instant when the tips touch the slot. Following this rule,

detection of the maximum gray level of the region of interest is employed to measure the

contact status. The average gray level of the region of interest is calculated from

∑∑= =

=r

i

c

jijp

rcG

1 1

1ˆ

where G is the average gray level of the region of interest, r and c are the number of

rows and columns of the region of interest in the image, ijp is the gray value of the pixel

at ith row and jth column in the region of interest in the image.


Figure 5-12 Variations of images during insertion

Figure 5-13 Contact value curve during insertion

A gradient search algorithm is employed to determine the location of the peak value.

Let kG and 1ˆ

+kG denote the gray level at k and k+1 step.

If kk GG ˆˆ1 ≥+ , then move the base structure one positive step in z-axis

direction towards the tips.

Else if kk GG ˆˆ1 <+ , then the contact is detected and stop searching.


The advantage of this method is that it only requires a single microscope to determine the

contact status in three-dimensional space. In addition, the contact status is detected based

a relative maximum gray level of images, which increases the robustness to the quality of

images and the changes of illuminations.

5.8 Experiments on automated micro-joining

In order to investigate the performance of the automated micro-joining method,

experiments have been conducted on the robotic microassembly workstation. Sub-micron

accuracy is required to join a micropart to another micropart in three-dimensional space.

Prior to the three-dimensional automated micro-joining operation, a designated

micropart have been grasped with a passive microgripper. Patterns of the reoriented

micropart, and the target base structure are selected as shown in figure 5-14. After

completion of grasping the micro-part, open loop control is applied to translate and rotate

the micropart to a designated position. The next step is to join the micropart to another

micropart.

Figure 5-14 Patterns of reoriented micropart and base structure


Figure 5-15 Automated micro-joining in three-dimensional space

First, the tips of the micropart are brought into focus by using the auto-focus method

introduced in Section 5.6. Figure 15 (a) shows the in-focus tips of the reoriented

micropart. As described in Section 3.1, a two-stage alignment strategy is utilized to insert

the tips of the micropart into the slot of the base structure. Figure 15 (b)-(d) shows the


automated micro-joining procedures. When the slot close to the tips of the micropart,

contact detection is carried out using the vision-based method referred in Section 5.7.

The last step in the assembly of the micropart is to release the micropart from the

microgripper, which is accomplished by commanding the base structure to move away

from the microgripper in the z-axis direction. Figure 5-16 shows the released three-

dimensional MEMS structure.

Figure 5-16 Automated joined micropart


Automated joining a micropart to a base structure, and then releasing the assembled

micropart from microgripper takes about 24 seconds. The total time to assemble a

micropart is dependent on the initial relative distance between the micropart and its target

base structure. The speed of the automated micro-joining is not optimized. The execution

time may be further reduced by using high-speed micromanipulator.

To test the success rate of the automated micro-joining methodology, repetitive tests

of the automated micro-joining tasks have been conducted. 46 micro-joining tasks are

attempted, where 36 joining tasks are successfully joined. The success rate is 78%. The

reason for most failures in automated micro-joining tasks is due to patterns cannot be

matched. One possible way to increase the success rate is to employ a more robust pattern

matching method. The success of pattern matching results is influenced by the lighting

conditions. In contrast, the auto-focus method and vision-based contact detection method

are robust to the lighting conditions, since they utilize the relative focus values or gray

levels of the images.

86

Chapter 6

Micro-Force Sensor Design for Microassembly

Microassembly and micromanipulation require measuring micro/nano-Newtons

forces in extremely high sensitivity. This chapter presents the development of an electron

tunneling micro-force sensor for the use in microassembly and micromanipulation tasks.

The electron tunneling force sensor has the potential to achieve extremely high sensitivity,

which makes it very suitable for micromanipulation tasks. The micro-force sensor

consists of flexible structural members, to which two electrodes are attached, which

deflect under the application of manipulation forces, and micro-actuators. A feedback

controller is utilized to maintain a constant tunneling current across the two electrodes,

thereby maintaining constant gap between the two electrodes. Measurement of the

voltage applied to the actuator allows the manipulation force to be determined. Design

and modeling of the force sensor in commercial available micro-fabrication processes are

addressed. Metal coating using sputter and focused ion beam coating methods are

investigated to lower the effective resistance across the electron tunnels, which is of

fundamental importance in the development of electron tunneling micro-force sensor.

6.1 Principle of electron tunneling micro-force sensor

In general, an electron tunneling force sensor consists of two conductive electrodes.

When the gap between the two electrodes is small enough, i.e., less than 1 nm, a

tunneling current may be established by imposing a bias voltage across the gap. To

measure the micro-force, one electrode of the force sensor is connected to a cantilever

beam, and the other electrode is connected to an actuator. The gap between the two

electrodes will change in response to a force exerted on the cantilever beam. To measure

Chapter 6 Micro-Force Sensor Design for Microassembly 87

the force, the actuator adjusts the gap between the two electrodes by translating one

electrode. Through the use of a feedback controller to drive the actuator, the gap and the

tunneling current are maintained at a fixed value, which makes the actuator follow the

displacement of the cantilever beam. Therefore, the voltage imposed on the actuator to

maintain a constant electrode gap indicates the force exerted on the microgripper. Since

the tunneling current is very sensitive to the variation of the gap width between the two

electrodes, the force sensor is capable of force measurement with extremely high

sensitivity.

Figure 6-1 shows the structure of an electron tunnel, which consists of two electrodes.

Electrode 1 is connected to a microgripper or micromanipulator. Electrode 2 is driven by

a micro-actuator. The tunnel width d is the distance from electrode 1 to electrode 2,

which is expressed as

tyyd −=

where y is the displacement of the electrode 1 and yt is the displacement of the tip on the

electrode 2. The displacement of the electrode 1 is introduced by external forces. When

the tunnel width is small enough, i.e., less than 1 nm, imposing a bias voltage across the

electron tunnel will establish a tunneling current i [62], which is written as

)(2 tyyoeii −κ−=

where io and κ are constants. The minus sign indicates that the tunneling current is

inversely proportional to the distance between the two electrodes. The above equation

shows that the tunneling current is proportional to the exponent of tunnel width. Hence,

the measurement of micro-force can be very sensitive.


Figure 6-1 Structure of an electron tunnel

To integrate the electron tunneling micro-force sensor into the microassembly system,

two different designs are investigated. In the first design, electron tunneling micro-force

sensors are integrated into a passive microgripper, and fabricated with PolyMUMPs [61]

micromachining process. The second design integrates an electron tunneling micro-force

sensor into a micro-probe, which is fabricated with SOIMUMPs [63] micromachining

process.

6.2 Micro-force sensor design based on PolyMUMPs

Figure 6-2 shows a passive microgripper integrated with two electron tunneling force

sensors. The passive microgripper consists of two jaws, two sets of flexible beams, and a

fixed pad. The two jaws are connected to the fixed pad through the flexible beams. When

the microgripper grasps a micropart, the two jaws deflect outwards. To measure the

grasping forces, one electrode of the micro-force sensor is connected to the jaw; the other

electrode is connected to a thermal actuator. A sharp tip is made on the thermal actuator

to reduce the contact area. A driving voltage V is applied to the thermal actuator as

indicated. The microgripper is connected to ground. When the two electrodes are very

close to the each other, an electron tunneling current will be established because of the


biasing voltage across the gap. A tunneling current i will flow from the wider arm of the

thermal actuator, through the electron tunnel and the passive microgripper, and finally be

measured by a sensing circuit.

Figure 6-2 Passive microgripper with two electron tunneling micro-force sensors

As shown in figure 6-2, the two sets of flexible beams are modeled as guided

cantilever beams. The relationship between the grasping force and the jaw displacement

in the y-axis direction is described as

yL

NEWHFy 3

3=

where Fy is the micro-force exerted on the upper jaw of the microgripper in the y-axis

direction, N is the number of flexible beams connected to the upper jaw, E is the Young’s

modulus of the material, W is the width of the beams, H is the thickness of the beams in

bending direction, L is the length of the beams, and y is the displacement of upper jaw in

the y-axis direction. To determine the micro-forces exerted on the microgripper, the

displacement of the electrode 2 must be measured.

As shown in figure 6-3, the thermal actuator in the electron tunneling force sensor

employs a U-beam structure. It has uniform material with varying geometry. The U-beam


structure consists of two arms: thin arm and wide arm. The thin arm has higher resistance

than the wide arm. The power consumption on each arm is proportional to its resistance.

With the same current, the thin arm consumes more power, and thus has higher

temperature than the wide arm. Therefore, the thin arm expands more than the wide arm,

which leads the actuator to bend upwards.

Figure 6-3 U-beam thermal actuator

The deflection of the thermal actuator is roughly proportional to the square of the

applied voltage. The model of thermal actuator is written as

2aVyt =

where yt is the deflection of the thermal actuator at the free end, a is a constant coefficient,

and V is the voltage applied to the thermal actuator. The coefficient a can be determined

from finite element analysis or experiments.

When the micro-force sensor operates in a constant tunnel width mode, the thermal

actuator displaces the same as the jaw of the microgripper in the y-axis direction.

Through the use of the models of the thermal actuator and the passive microgripper, the

micro-force exerted on the jaw of the microgripper can be written as

23

3aV

LNEWHFy =

To determine the micro-forces exerted on the microgripper, the models of the

microgripper and the thermal actuator are identified. The model of the microgripper is


determined from the stiffness equation of guided cantilever beam. In this paper,

PolyMUMPs process is employed to fabricate the micro-force sensor. The material

properties and geometry parameters used in this paper are listed in table I. The calculated

stiffness of one set of flexible beams in the microgripper is 9.77 N/m.

TABLE I. PARAMETRES OF MICROGRIPPER

Young's modulus E (Pa)

Beam width W (m)

Beam thicknessH (m)

Beam length L (m)

Number of beams N

Stiffnessk (N/m)

1.69E+11 2E-6 2E-6 9.4E-5 3 9.77 Finite element analyses are employed to determine the model of the thermal actuator.

table II offers the different displacements of the thermal actuator at different driving

voltages.

TABLE II. RESPONSE OF THERMAL ACTUATOR

Voltage (V) 1 2 3 4 5Displacement (um) 0.1264 0.5013 1.126 2.001 3.126

Based on the simulation results in table II, the model of thermal actuator is identified

using a least square polynomial fit method. Figure 6-4 shows the result of the identified

model. The polynomial fit provided the results of a = 0.125 with the residual R = 0.00187.


Figure 6-4 Thermal actuator deflections

Based on the models of the thermal actuator and the microgripper, the model of the

micro-force sensor is obtained as

222.1 VFy =

A feedback controller is employed to operate the micro-force sensor in a constant

tunnel width mode, i.e., driving the electrode 1 on the thermal actuator to follow the

displacement of the electrode 2 on the jaw of the microgripper to maintain a constant

electron tunnel width. Figure 6-5 shows the schematic of the feedback controller. The

tunneling current i is measured by a current amplifier, then sent to a logarithmic amplifier,

and converted to a voltage ul, which is proportional to the tunnel width of the micro-force

sensor. Then the voltage ul is compared with a pre-defined voltage us, which represents

the set point of the tunneling current. The error signal e is processed by a PID controller.


The output voltage of the PID controller is applied to the thermal actuator to keep the

tunneling current staying at the set point.

The parameters of the PID controller are selected to form a negative feedback loop. If

the tunneling current is larger than the value pre-defined by the voltage us, then the

voltage applied to the thermal actuator tends to decrease, which moves the tunnel tip

away from the electrode 2 on the jaw of the microgripper, and vice versa. Therefore, the

tunnel tip on electrode 1 can accurately follow the displacement of the jaw of the

microgripper in the y-axis direction.

Figure 6-5 Feedback controller for electron tunneling micro-force sensor

LMC6001

Rx Rf

Vo

Current Amplifier

Vi

Figure 6-6 Current amplifier for electron tunneling force sensor

Because the tunneling current can be lower than several nano or pico-Amperes, the

current amplifier in the feedback controller should have an extremely high resolution.

The diagram of current amplifier is shown in figure 6-6. A biasing voltage is applied

across the electron tunnel. The effective resistance of the electron tunnel is xR , which


may vary from infinity to several mega-Ohms. The tunneling current is connected to the

negative input of an op-amp, LMC6001. This op-amp has an extremely low input current

of 25 fA [64]. The tunneling current is picked up by a feedback resister GR f 1= . The

biasing voltage across the feedback resister is smaller than 25 μV.

When the tunneling tip on electrode 1 is very close to the surface of electrode 2,

stiction forces might arise. Symmetric deployment of two thermal actuators can cancel

the effect of the stiction forces. Figure 6-7 shows the fabricated microgripper integrated

with micro-force sensors.

Figure 6-7 Microgripper integrated with micro-force sensors

The tunneling tip in the electron tunnel force sensor must be sharp enough to establish

a reliable electron tunneling current. The fabrication of a sharp tip using PolyMUMPs

process is investigated. Two types of tunnelling tips, as shown in figure 6-8, are


fabricated with structure layer of Poly1 in PolyMUMPs. The fabricated micro-tips are

shown in figure 6-9. The design with an acute angle of 11.4o formed a very sharp tip. The

minimum width of the tunnel tip was less than 100 nm.

Figure 6-8 Design of tunnel tips, (a) right angle, (b) acute angle

Figure 6-9 Fabricated tunnel tips, left: right angle, right: cute angle

A problem in this design is that the effective resistance between the two electrodes is

extremely high. When the two electrodes contact with each other through their sidewalls,


the tunneling current cannot be detected. Coating a layer of metal onto the contact surface

would significantly decrease the effective resistance. However, since the Poly1 layer is

very close to the substrate of the MEMS chip, coating a layer of metal onto the Poly1

may cause the movable structure sticking onto the substrate of the MEMS chip. One

approach to address this problem is to switch to SOI (silicon on isolator) micromachining

fabrication process. Another potential problem in this design is that the thermal actuator

has a relative low bandwidth, which might lead to slow response in the feedback control

loop. In addition, thermal fluctuation could bring noise into the micro-force

measurements. Hence, another electron tunneling micro-force sensor that employs

capacitive actuator is developed with SOIMUMPs micromachining fabrication process.

6.3 Micro-force sensor design based on SOIMUMPs

Compared with PolyMUMPs process, SOIMUMPs process allows for capacitive

actuator generating larger driving forces. The released function layer in SOIMUMPs is

suspended in the air, so that coating a layer of metal will not cause trouble to the movable

features. Moreover, an extended-out feature can be fabricated by removing the substrate

layer in SOIMUMPs, which is useful for integration of the micro-force sensor into

microgripper or micromanipulator.

In this section, an electron tunneling micro-force sensor is integrated with a pushing

probe, which can be used in pushing-based micromanipulation. To manipulate other

micro-objects, the pushing probe is extended out of the edge of the substrate. To fabricate

this extending out pushing probe, cut through features are designed on the MEMS chip.

As shown in figure 6-10, two rectangular cut through features are employed to etch

though the entire MEMS chip. The left and right parts of the MEMS chip only connect to


each other through several temporary connectors. Each temporary connector is a beam

with dimensions of 25×5×100 μm. Ruptures of the temporary connectors can detach the

left part of the MEMS chip along the breaking edges. To ensure not damaging the

pushing probe during break the MEMS chip, the width of the cut through features is set

to 200 μm.

Figure 6-10 Cut through features for extending out pushing probe

Figure 6-11 shows the structure of the pushing probe and the micro-force sensor.

Electrode2, is attached to the pushing probe. Another electrode labeled as Electrod1 is

placed close to Electrode2. When the two electrodes are close enough to each other, a

tunneling current may be established by applying a biasing voltage across the two

electrodes. Different from the micro-force sensor design in PolyMUMPs, this micro-force

sensor works in a force-balanced mode. When an external force Fe is exerted on the

pushing probe, the Electrode2, together with the pushing probe, will move away from the

electrode1. At the same time, a lateral comb drive capacitive actuator applies a force Fc in

the opposite direction to push the Electrode2 to approach the Electrode1. When the two


forces exerted on the pushing probe are balanced, the two electrodes will remain at a

constant distance from each other, which will lead to a constant electron tunneling

current. In this design, the capacitive actuator has higher bandwidth than a thermal

actuator, and is not affected by the thermal fluctuation noise. The device is fabricated

with the SOIMUMPs micromachining process. All the function structures are made in

SOI layer, a 25-μm-thick doped single-crystal-silicon layer. The SOI layer is mounted on

top of the substrate through an isolator layer. Underneath the movable features in the SOI

layer, the isolator and substrate are removed by etching. The two electrodes are

suspended in air, which makes it easier to coat metal onto the contact surfaces.

Figure 6-11 Pushing probe integrated with electron tunneling micro-force sensor


Figure 6-12 Compliant beam dimension in micro-force sensor

Four compliant beams support the pushing probe. Since they are symmetrically

deployed with respect to the pushing probe, the four compliant beams are modeled as

guided cantilever beams. The dimensions of a compliant beam are shown in figure 6-12.

The total stiffness of the compliant beams k is determined from

3

3

lNEwhk =

where N is the number of compliant beams, E is the Young’s modulus of the SOI

material, w is the width of one beam, h is the height of one beam, and l is the length of

one beam. The parameters used in this design is listed in table III.


TABLE III. PARAMETRES OF COMPLIANT BEAMS IN PUSHING PROBE

Young's modulus E (Pa)

Beam width w (m)

Beam height h (m)

Beam length l (m)

Number of beams N

Stiffnessk (N/m)

1.00E+11 25E-6 4E-6 400E-6 4 10

The electrostatic forces generated by the lateral comb drive capacitive actuator is

expressed as

2

2V

gwN

F ac

ε=

where 600=aN is number of comb fingers in the actuator, 1121085.8 −−×=ε Fm is the

permittivity of air, mw 61025 −×= is the depth of the fingers, mg 6103 −×= is the gap

between the fingers, and V is the voltage to drive the actuator. Hence, we have

281021.2 VFc−×=

When the compliant beams stay in their rest position, the initial gap between the two

electrodes is several microns. In order to establish an electron tunneling current, the

electrostatic actuator must drive the electrode2 to a position extremely close to the

electrode1, i.e., less than 1 nm. If the initial gap between the two electrodes is 0x , then an

electrostatic force 00 kxFc = should be applied to close the initial gap. When an external

force eF is exerted onto the pushing probe, the gap between the two electrodes would

increase, which will dramatically decrease the electron tunneling current. To maintain a

constant electron tunneling current, the electrostatic force applied to electrode2 should be

ecc FFF += 0 .

An important problem in the design electron tunneling micro-force sensor is to

generate and detect the tunneling current. The design of the electrodes is shown in figure

6-13 (a). Each electrode has an acute angle of 43.6o. The gap between the two electrodes


in the layout design file is 3 μm. The corresponding fabricated features of the electrodes

are shown in figure 6-13 (b). This figure is taken with the optical microscope introduced

in Chapter 2. Measuring from the image, the actual gap between the two electrodes is 19

pixels. Since the scale of the microscope is 0.3335 μm/pixel, the actual gap is 6.33 μm.

Different MEMS chips with the same design are examined under the microscope. The

difference between the design and the fabrication result is caused by the over etching in

the microfabrication process, which can vary from one fabrication to another. Hence, the

initial gaps in different electron tunneling micro-force sensors are different.

Figure 6-13 Design and fabrication of electron tunneling tips

Since the two electrodes are fabricated with doped single crystal silicon, the effective

resistance of the electron tunnel is too high to generate a detectable tunneling current. In

order to decrease the effective resistance, sputter coating is utilized to deposit a layer of

gold film onto the surface of the two electrodes. Figure 6-14 (a) shows an etched


electrode without sputter coating. The tip of the etched electrode is rounded. Figure 6-14

(b) is a sputter-coated electrode. The sidewall of the electrode in figure 6-14 (b) is

covered with a layer of gold film. The surface of the sidewall is smoother than the non-

coated surface. With the coated gold film, the effective resistance is dramatically

decreased. When the gap between the two electrodes closes, a tunneling current is

detected. However, the mechanical strength of the sputter coating is very poor. After one

to three times of gap closures, the coated gold film is worn out. In figure 6-14 (c), gold

film coated on the upper part of the sidewall has fallen off. When the gold film is worn

out, the effective resistance becomes extremely high again, and the electron tunneling

current cannot be detected.

Figure 6-14 Sidewallsof electrodes (a) non-coated b) sputter coated(c) worn out

Another approach, focused ion beam (FIB) coating, is investigated to decrease the

effective resistance between the two electrodes. High-energy platinum ion beam is

focused onto the electrodes, such that a thin layer of platinum is deposited to the contact

surfaces of the electrodes. Figure 6-15 shows a high-magnification SEM (scanning

electron microscopy) picture of an FIB coated sidewall of an electrode. The SOIMUMPs

micro-fabrication process employs deep reactive-ion etching (DRIE) to fabricate the


electrode. The roughness of the electrode sidewall can be up to tens of nanometers. The

coated platinum layer is not thick enough to cover the rough surface of the sidewall. In

order to test the performance of the FIB coating, a DC (direct current) voltage is applied

across the lateral comb electrostatic actuator to close the initial gap between the two

electrodes. As the gap closes, an effective resistance between the two electrodes is

detected by a multimeter (Fluke 87 III). When the two electrodes firmly contact with

each other, the contact resistance is from 4.8 to 5.3 MΩ. Before the firm contact, the

contact resistance varies from 4.8 MΩ to over 40 MΩ. After many times of firm contact

between the two electrodes, the effective resistance does not change too much. This result

shows that the FIB coating has a strong mechanical strength, and can reduce the effective

resistance between the two electrodes to a detectable level.

Figure 6-15 Focused ion beam coating on sidewall of electrode


The possible reason for the big variation of the contact resistance can be the vibration

from the test table. The vibration will cause the gap between the two electrodes to

change, which will finally change the effective contact resistance. Another possible

reason is the moisture in air. Hence, use of an anti-vibration table and placing the sensor

into a vacuum chamber, or control the operation environment could solve this problem.

This section provides an effective approach to integrate micro-force sensor into

micromanipulator utilizing commercial micro-fabrication process. In order to lower the

effective resistance across the electron tunnel, focused ion beam method is employed to

coat a durable layer of metal. This work provides valuable experiences to develop

sensitive micro-force sensors for microassembly and micromanipulation tasks.

105

Chapter 7

Conclusion and Discussions

7.1 Thesis summary

This thesis presents research work in robotic microassembly, a promising approach to

fabricate the next generation of MEMS devices. Several key techniques in robotic

microassembly are studied in this thesis. A novel adhesive mechanical micro-fastener is

proposed to assemble microparts with high positioning accuracy, high mechanical

strength, and reliable electrical connections. In order to manipulate microparts with

multiple degrees of freedom and high accuracy, a hybrid micromanipulation strategy is

proposed to assemble microparts. Fully automated pick-and-place microassembly is

developed based on computer vision. High accuracy visual servo control and vision-

based contact sensor are developed to facilitate the automated microassembly in three-

dimensional space. This section summarizes the thesis work in robotic microassembly.

Micro-fastener design is of fundamental importance towards successful

microassembly of complex, multiple functional micro-devices with high accuracy. The

micro-fastener should have a simple structure, so that the microparts can be easily

assembled with high accuracy. The micro-joint should have strong mechanical strength to

fix the microparts. In some microassembly applications, e.g., micro-devices with

assembled sensors, it is necessary for the micro-fastener to provide reliable electrical

connections between the assembled microparts. This thesis presents a novel design of

micro-fastener, which consists of an adhesive bonding and a mechanical joint mechanism.

The adhesive bonding provides reliable mechanical and electrical joints between the

assembled microparts. The mechanical joint mechanism has self-alignment capability, so

Chapter 7 Conclusion and Discussions 106

that the microassembly may achieve high positioning accuracy with a simple assembly

operation. To create micro-joints with adhesive bonding, robotic manipulation of micro-

sized adhesive droplets is necessary. A micro-adhesive droplet manipulator is developed

to pick up and deposit adhesive droplets. The surface tension effect is utilized in the

droplet manipulator design to control the sizes of manipulated adhesive droplets.

Experimental results show that the area of deposited adhesive droplet can be as small as

4×4 μm2.

Another fundamental problem in microassembly is to manipulate microparts with

multiple degrees of freedom, as well as achieve high positioning accuracy. Pick-and-

place and pushing-based manipulation are two general approaches used in microassembly.

Pick-and-place micromanipulation is able to manipulate a micropart with multiple

degrees of freedom through three-dimensional space. Pushing-based manipulation can

finely adjust the positions and orientations of manipulated microparts. Compared with the

pick-and-place micromanipulation, the pushing-based manipulation has the potential to

achieve higher positioning accuracy, but cannot globally manipulate microparts in three-

dimensional space. In this thesis, a hybrid micromanipulation strategy is proposed to

assemble microparts with high accuracy and global manipulation capability. The hybrid

manipulation strategy consists of two sequential sub-steps: pick-and-place manipulation

and pushing-based operation. This manipulation strategy first globally positions a

micropart with pick-and-place manipulation, and then pushes the micropart to finely

adjust its position and orientation. In this way, an accurate and highly flexible

microassembly is achieved. This hybrid manipulation requires micro-fastener provide

both temporary connection and permanent joint between the assembled microparts, which


is achieved by the adhesive mechanical fastner. A three-dimensional rotary MEMS

mirror is assembled using the hybrid manipulation strategy, which demonstrates the high

accuracy and high flexibility of this approach.

Full automation of robotic microassembly is very important to increase productivity,

improve reliability, and lower assembly cost. However, automated microassembly with

high positioning accuracy in three-dimensional space is challenging task. This thesis

proposed a vision-based automated microassembly approach to manipulate microparts

with high accuracy in large three-dimensional space. Sequential microassembly tasks are

carried out under a high-magnification optical microscope. To address the issue of low

depth of field in high-magnification optical microscope, special multiple stage alignment

strategies are utilized to perform the micro-grasping and micro-joining tasks. During the

automated micro-grasping tasks, auto-focusing method and compliant structures are

utilized to align micro-gripper with micropart in the optical axial direction of the

microscope. Visual servo control is employed to align micro-features in the image plane.

To increase the alignment accuracy, a novel fine alignment visual servo controller is

developed to carry out the micrograsping tasks. The deflections of the microgripper jaws

provide the feedback signals to the visual servo controller, which effectively eliminates

the errors from template preparations. Experimental results show that the average

alignment accuracy of the fine visual servo controller is –0.07 μm, with a standard

deviation of 0.12 μm.

In order to accurately join microparts, accurate contact detection is necessary. Using a

single microscope to detect the contact status between microparts in three-dimensional

space is a challenging problem. This thesis proposes a novel contact sensor based on


computer-vision to address this problem. In the micro-joining process, the joint features

on the micropart deflect, which cause the image brightness around the joint features to

vary with different joining depth. This thesis proposed a contact function based on the

image brightness. When two microparts contact to each other, the contact function will

reach its maximum value. Compared with other methods, detection of the peak value is

more robust than to measure the contact status through comparison the value with a pre-

defined threshold. The resolution of the vision-based contact sensor is determined by the

resolution of the encoder in the vertical axis of the robot.

Fully automated micro-grasping and micro-joining tasks have been successfully

conducted. The time to complete a successful micro-grasping task is as short as 7.9

seconds. The time to automated join a micropart is 24 seconds. Note that the speed of the

automated control can be further optimized. The success rate of automated

microassembly has been tested through repetitive experiments. Automated micro-

grasping task has a success rate of 94%. Automated micro-joining has a success rate of

78%. This can be further improved by using an anti-vibration table and more robust

computer vision algorithms.

Another important approach to improve the performance of automated

microassembly is to measure and control the interaction forces between the microparts.

Since the interaction forces in microassembly are very small, extremely sensitive micro-

force sensors have to be integrated into the micromanipulation systems. This thesis

proposes two types of electron tunneling micro-force sensors and integrated them into

microgripper or micro-probe. The electron tunneling micro-force sensor has the potential

to achieve extremely high resolution, which is suitable for the application in


microassembly and micromanipulation. Two micro-fabrication processes, PolyMUMPs

and SOIMUMPs, are employed to fabricate the electron tunneling micro-force sensors.

Both of these approaches have the problem of high effective resistance across the

electron tunnel. Sputter coating and focused ion beam coating are investigated to

decrease the effective resistance. Experiments show that the focused ion beam coating

can deposit a durable layer of metal, which effectively decrease the effective resistance.

This thesis studies the design of electron tunneling micro-force sensor with PolyMUMPs

and SOIMUMPs fabrication process, and tests the method to decrease the effective

resistance across the electron tunnel, which provides valuable experiences to develop

highly sensitive micro-force sensors with commercial micro-fabrication processes.

7.2 Summary of contributions

This thesis successfully addresses several fundamental problems in robotic

microassembly, such as high-performance micro-fastener design, flexible and accurate

micromanipulation strategy, and high-accuracy vision-based automated control. This

work provides an effective approach to fabricate the next generation of MEMS devices,

which may have complex three-dimensional structures, hybrid and incompatible

materials, and highly integrated unique functions. By using the robotic microassembly

technology in this thesis, prototypes of micro-devices can be fabricated in a fast and cost-

effective manner. Moreover, the vision-based automated control may effectively promote

the productivity and success rate of the microassembly process, which is necessary to

make complex three-dimensional MEMS devices commercially viable. Therefore, this

thesis provides a solid approach to fabricate the next generation of micro-devices. This

section summarizes the main contributions of this thesis, which include:


Development of a novel adhesive mechanical fastener to attach microparts with high

accuracy, high mechanical strength, and reliable electrical conductivity. Surface

tension effect is employed to develop an adhesive droplet micromanipulator to pick

up and deposit micro-size adhesive droplets, and control their sizes.

Implementation of a hybrid micromanipulation strategy to assemble microparts with

high accuracy and multiple degrees of freedom. Pick-and-place micromanipulation is

employed to globally manipulation microparts, followed by fine adjustment of their

positions and orientations through pushing-based manipulation. A three-dimensional

rotary micro-mirror is assembled to demonstrate the feasibility of this approach.

Employment of visual servo control and multiple stage strategy to accurately align

micro-features in three-dimensional space. A special fine visual servo controller is

developed for automated micrograsping to increase the average alignment accuracy as

high as 0.07 μm.

Development of a novel vision-based contact sensor for the use in three-dimensional

micro-joining tasks. A contact function is proposed based on single microscopy

image. The contact function reaches its maximum value when contact happens, which

is robust to image noises and illumination variations.

Implementation of fully automated micro-grasping and micro-joining tasks with high

throughput and high success rate. The times to finish micro-grasping and micro-

joining tasks are 7.9 and 24 seconds, respectively. Automated micro-grasping and

micro-joining have success rates of 94% and 78%, respectively.

Design of electron tunneling micro-force sensor for the use in microassembly and

micromanipulation. Two different designs are implemented in PolyMUMPs and


SOIMUMPs micro-fabrication processes. Models of the micro-force sensors are

obtained. To reduce the effective resistance of the electron tunnel, metal coating

techniques are investigated.

7.3 Recommendations for future work

This thesis presents key technologies in robotic microassembly, such as the design of

micro-fastener, advanced micromanipulation strategy, and fully automated control. This

work provides an effective approach to fabricate the next generation of complex micro-

devices. This section presents several recommendations for future work, so that the

performance of robotic microassembly technology can be further improved.

In this thesis, the adhesive mechanical fastener utilizes adhesive bonding and

mechanical fastener to provide accurate, strong and reliable connections between the

assembled microparts. However, the shape of deposited adhesive droplet can only be

circular due to the surface tension effect. Some microassembly tasks might require

depositing other shapes of adhesive spots. Better control of the deposited adhesive shape

may help to expand the application of robotic microassembly and enhance the quality of

adhesive bonding.

In the hybrid micromanipulation strategy, pushing-based manipulation is important to

accurately adjust the positions and orientations of the manipulated microparts. Hence,

automated pushing-based manipulation needs to be developed in the future work.

Compared with pick-and-place micromanipulation, micro-force measurement and control

is more important to pushing-based manipulation. This thesis provides the design of

electron tunneling micro-force sensors, and obtains a preliminary experimental result.


This work can be expanded and utilized in the automation of pushing-based

micromanipulation.

113

References [1] Q. Bai, K. Wise, and D. Anderson, “A high-yield microassembly structures for

three-dimensional microelectrode array,” IEEE Transactions on Biomedical Engineering, vol. 47, no. 3, pp. 281-289, March 2000.

[2] J. Sin, W. Lee, D. Popa, and H. Stephanou, “Assembled Fourier transform micro-

spectrometer,” Proceedings of the SPIE - The International Society for Optical Engineering, vol. 6109, p. 610904, January 2006.

[3] N. Dechev, W. Cleghorn, and J. Mills, “Microassembly of 3-D micro-structures

using a compliant, passive microgripper,” Journal of Microelectromechanical Systems, vol. 13, no. 2, pp. 176-189, April 2004.

[4] A. Singh, D. Horsely, M. Cohn, A. Pisano, and R. Howe, “Batch transfer of

microstructures using flip-chip solder bonding,” IEEE Journal of Microelectromechanical Systems, vol. 8, no. 1, pp. 27-33, March 1999.

[5] T. Ebefors, J. Ulfstedt-Mattsson, E. Kalvesten, and G. Stemme, “3D

micromachined devices based on polymide joint technology,” SPIE Symposium on Microelectronics and MEMS, Gold Coast, Queensland, Australia, SPIE vol. 3892, pp. 118-132, October 1999.

[6] K. Harsh, V. Bright, and Y. Lee, “Solder self assembly for three-dimensional

microelectromechanical systems,” Sensors and Actuators, vol. 77, pp. 237-244, November 1999.

[7] K. Lai, A. Hui, and W. Li, “Non-contact batch micro-assembly by centrifugal

force,” Proceedings of the IEEE Micro Electro Mechanical Systems (MEMS), pp. 184-187, January 2002.

[8] J. Zou, J. Chen, C. Liu, and J. Schutt-Aine, “Plastic deformation magnetic

assembly (PDMA) of out-of-plane microstructures: technology and application,” IEEE Journal of Microelectromechanical Systems, vol. 10, no. 2, pp. 302-309, June 2001.

[9] K. Bohringer, K. Goldberg, M. Colm, R. Howa, and A. Pisano, “Parallel

microassembly with electrostatic force fields,” Proceedings. 1998 IEEE International Conference on Robotics and Automation, vol. 2, pp. 1204-1211, Leuven, Belgium, May 1998.

[10] S. Ralis, B. Vikramaditya, and B. Nelson, “Micropositioning of a weakly

calibrated microassembly system using coarse-to-fine visual servoing strategies,” IEEE Transactions on Electronics Packaging Manufacturing, vol. 23, no. 2, April 2000.

References 114

[11] A. Das, P. Zhang, W. Lee, D. Popa, and H. Stephanou, “μ3: multiscale, deterministic micro-nano assembly system for construction of on-wafer microrobots,” Proceedings - IEEE International Conference on Robotics and Automation, pp. 461-466, Roma Italy, April 2007.

[12] N. Dechev, L. Ren, W. Liu, W. Cleghorn, and J. Mills, “Development of a 6

degree of freedom robotic micromanipulator for use in 3D MEMS microassembly,” Proceedings - IEEE International Conference on Robotics and Automation, vol. 2006, pp. 281-288, Orlando, FL, US, May 2006.

[13] M.C. Carrozza, A. Eisinberg, A. Menciassi, D. Campolo, S. Micera, and P. Dario,

“Towards a force-controlled microgripper for assembling biomedical microdevices,” Journal of Micromechanics and Microengineering, vol. 10, no. 2, pp. 271–276, June 2000.

[14] M. Kemper, “Development of a tactile low-cost microgripper with integrated

force sensor,” Proceedings of the 2004 IEEE International Conference on Control Applications, vol. 2, pp. 1461–1466, September 2004.

[15] J. Agnus, P. De Lit, C. Clevy, and N. Chaillet, “Description and performances of

a four-degrees-of-freedom piezoelectric gripper,” Proceedings of the 2003 IEEE International Symposium on Assembly and Task Planning (ISATP2003), pp. 61–67, July 2003.

[16] Y. Haddab, N. Chaillet, and A. Bourjault, “A microgripper using smart

piezoelectric actuators,” Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000), vol. 1, pp. 659–664, October-November 2000.

[17] B.E. Volland, H. Heerlein, and I.W. Rangelow, “Electrostatically driven

microgripper,” Microelectronic Engineering, vol. 61-62, pp. 1015-1023, July 2002.

[18] C.J. Kim, A.P. Pisano, R.S. Muller, and M.G. Lim, “Polysilicon Microgripper,”

Sensors and Actuators, A: Physical, vol. 33, no. 3, pp. 221-227, June 1992.

[19] J. H. Comtois, V. M. Bright, and M. W. Phipps, “Thermal microactuators for surface-micromachining processes,” Proceedings of SPIE - The International Society for Optical Engineering, vol. 2642, pp. 10–21, October 1995.

[20] D.M. Burns, and V. M. Bright, “Design and performance of a double hot arm

polysilicon thermal actuator,” Proceedings of SPIE - The International Society for Optical Engineering, vol. 3224, pp. 296–306, September 1997.

[21] C. H. Pan, C. Chang, and Y. Chen, “Design and fabrication of an electro-thermal

microactuator with multidirectional in-plane motion,” Journal of

References 115

Microlithography, Microfabrication, and Microsystems, vol. 4, no. 3, pp. 33008-1-15, July 2005.

[22] A.P. Lee, D. R. Ciarlo, P. A. Krulevitch, S. Lehew, J. Trevino, and M. A.

Northrup, “A practical microgripper by fine alignment, eutectic bonding and SMA actuation,” Sensors and Actuators A (Physical), vol. A54, no. 1-3, pp. 755-759, June 1996.

[23] Y. Fu, H. Du, W. Huang, S. Zhang, and M. Hu, “TiNi-based thin films in MEMS

applications: A review,” Sensors and Actuators A (Physical), vol. 112, no. 2-3, pp. 395–408, May 2004.

[24] K. Tsui, A. Geisberger, M. Ellis, and G. Skidmore, “Micromachined end-effector

and techniques for directed MEMS assembly,” Journal of Micromechanics and Microengineering, vol. 14, no. 4, pp. 542–549, April 2004.

[25] R. Prasad, K.-F. Bohringer, and N.C. MacDonald, “Design, Fabrication, and

Characterization of SCS Latching Snap Fasteners for Micro Assembly,” Proceedings of ASME International Mechanical Engineering Congress and Exposition(IMECE), vol. 57-2, pp. 917-923, November 1995.

[26] L. Zhou, J.M. Kahn, and K.S.J. Pister, “Corner-Cube Retroreflectors Based on

Structure-Assisted Assembly for Free-Space Optical Communication,” Journal of Microelectromechanical Systems, vol. 12, no. 3, pp. 233-242, June 2003.

[27] N. Dechev, J.K. Mills, and W.L. Cleghorn, “Mechanical Fastener Designs for Use

in the Microassembly of 3D Microstructures,” Proceedings of the ASME International Mechanical Engineering Congress IMECE, pp. 447-456, November 2004.

[28] P. Zhang, M. Mayyas, W. Lee, D. Popa, P. Shiakolas, H. Stephanou, and J. Chiao,

“An active locking mechanism for assembling 3D micro structures,” Proceedings of the SPIE - The International Society for Optical Engineering, vol. 6414, p. 641425 (8 pp.), Adelaide, SA, Australia, December 2006.

[29] M.B. Cohn, “Assembly Techniques for Microelectromechanical Systems”, Ph.D.

Thesis, Department of Electrical Engineering and Computer Science, University of California, Berkeley, US, 1997.

[30] E. Shimada, J.A. Thompson, J. Yan, R. Wood, and R.S. Fearing, “Prototyping

MilliRobots Using Dextrous Microassembly and Folding,” Proceedings of the ASME International Mechanical Engineering Congress and Expo (IMECE / DSCD), vol. 69-2, pp. 933-940, Orlando, Fl. US, Nov. 2000.

References 116

[31] Y. Zhou, B. Nelson, and B. Vikramaditya, “Integrating Optical Force Sensing with Visual Servoing for Microassembly,” Journal of Intelligent and Robotic Systems, Vol. 28, no. 3, pp. 259-276, 2000.

[32] J. A. Thompson, and R. S. Fearing, “Automating Microassembly with Ortho-

tweezers and Force Sensing,” Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Vol. 3, pp. 1327-1334, Maui, HI, US, October-November 2001.

[33] A. Ferreira, C. Cassier, and S. Hirai, “Automatic Microassembly System Assisted

by Vision Servoing and Virtual Really,” IEEE/ASME Transactions on Mechatronics, Vol. 9, No. 2, pp. 321-333, June 2004.

[34] W. Zesch, and R. S. Fearing, “Alignment of Microparts Using Force Controlled

Pushing,” Proceedings of SPIE - The International Society for Optical Engineering, Vol. 3519, pp. 148-156, November 1998.

[35] K. Bohringer, R. Fearing, and K. Golgberg, Chapter 9.55 Micro-assembly, in The

Handbook of Industrial Robotics, Second Edition, p. 1045.

[36] W. Zesch, M. Brunner, and A. Weber, “Vacuum Tool for Handling Micro-Objects with a Nano-Robot,” Proceedings 1997 IEEE International Conference on Robotics and Automation, vol. 2, pp. 1761-1766, April 1997.

[37] W. Zesch, and R. Fearing, “Alignment of microparts using force controlled

pushing,” Proceedings of SPIE - The International Society for Optical Engineering, vol. 3519, pp. 148-156, November 1998,

[38] G. Greitmann, and R. Buser, “Tactile microgripper for automated handling of

microparts,” Sensors and Actuators A (Physical), vol. A53, no. 1-3, pp. 410-415, May 1996.

[39] S. Fahlbusch, A. Shirinov, and S. Fatikow, “AFM-based micro force sensor and

haptic interface for a nanohandling robot,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and System, vol. 2, pp. 1772-1777, Septermber-October 2002.

[40] J. Breguet, S. Henein, R. Mericio, and R. Clavel, “Monolithic piezoceramic

flexible structures for micromanipulation,” in Proceedings of International Precision Engineering Seminar, vol. 2, pp. 397-400, 1997.

[41] D. Kim, B. Kim, and H. Kang, “Development of a piezoelectric polymer-based

sensorized microgripper for microassembly and micromanipulation,” Microsystem Technologies, vol. 10, no. 4, pp. 275-280, May 2004.

References 117

[42] H. Woo, H. Byoung, S. Young, H. Stephanou, A. Sanderson, G. Skidmore, and M. Ellis, “Micropeg manipulation with a compliant microgripper,” in Proceedings of IEEE International Conference on Robotics and Automation, vol. 3, pp. 3213-3218, September 2003.

[43] M. Grerninger, and B. Nelson, “Vision-based force sensing at nanoNewton

scales,” in Proceedings of the SPIE - The International Society for Optical Engineering, vol. 4568, pp. 78-89, October 2001.

[44] Y. Anis, J. Mills, and W. Cleghorn, “Vision-based measurement of

microassembly forces,” Journal of Micromechanics and Microengineering, vol. 16, no. 8, pp. 1639-1652, August 2006.

[45] Y. Zhou, B. Nelson, and B. Vikramaditya, “Integrating optical force sensing with

visual servoing for microassembly,” Journal of Intelligent and Robotic Systems: Theory and Applications, vol. 28, no. 3, pp. 259-279, Jul 2000

[46] R. Fearing, “Survey of sticking effects for micro parts handling,” in Proceedings.

1995 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 212-217, August 1995.

[47] X. Tao, H. Cho, and Y. Cho, “Microassembly of peg and hole using active

zooming,” In proceedings of SPIE - The International Society for Optical Engineering, vol. 6052, p. 605204, December 2005.

[48] H. Yamamoto, and T. Sano, “Study of micromanipulation using stereoscopic

microscope,” IEEE Transactions on Instrumentation and Measurement, vol. 51, no. 2, pp. 182-187, April 2002.

[49] S. Lee, K. Kim, D. Kim, J. Park, and G. Park, “Recognizing and tracking of 3D-

shaped micro parts using multiple visions for micromanipulation,” in Proceedings of International Symposium on Micromechatronics and Human Science, pp. 203-210, September 2001.

[50] S. Ralis, B. Vikramaditya, and B. Nelson, “Visual servoing frameworks for

microassembly of hybrid MEMS,” in Proceedings of the SPIE - The International Society for Optical Engineering, vol. 3519, pp. 70-79, Boston, MA, USA, November 1998

[51] B. Tamadazte, S. Dembele, G. Fortier, and N. Le Fort-Piat, “Automatic

micromanipulation using multiscale visual servoing,” in Proceedings of IEEE International Conference on Automation Science and Engineering, pp. 977-982, Arlington, VA, USA, Aug 2008

[52] Y. Anis, J. Mills, and W. Cleghorn, “Visual-servoing of a six-degree-of-freedom

robotic manipulator for automated microassembly task execution,” Journal of

References 118

Microlithography, Microfabrication, and Microsystems, vol. 7, no. 3, pp. 33017-33025, July 2008.

[53] J. Feddema, and R. Simon, “Visual servoing and CAD-driven microassembly,”

IEEE Robotic and Automation Magazine, vol. 5, no. 4, pp. 18-24, December 1998.

[54] National Instrument, NI Vision Development Module, http://www.ni.com/wision/vdm.htm.

[55] J. Faure, L. Noirie, and E. Ollier, “A 8×8 all optical space-switch based on a

novel 8×1 MOEMS switching module,” OFC 2001, Anaheim, USA, March 2001.

[56] Toshiyoshi, H., and Fujita, H., "Electrostatic micro torsion mirrors for an optical switch matrix," Journal of Microelectromechanical Systems, Vol. 5, no. 4, pp. 231-237, December 1996.

[57] Yasseen, A. A., Mitchell, J. N., Klemic, J. F., Smith, D. A., and Mehregany, M.,

"A rotary electrostatic micromotor 1×8 optical switch," IEEE Journal of Selected Topics in Quantum Electronics, Vol. 5, no. 1, pp. 26-32, January-February 1999.

[58] Grade, J. D., and Jerman, H., "MEMS electrostatic actuators for optical switching

applications," OFC 2001, WX2/1-3, Vol.3, Anaheim, USA, March 2001.

[59] Tu, C., Fanchiang, K., and Liu, C., "A 1xN rotary vertical micro mirror for optical switching applications," in Proceedings of the SPIE - The International Society for Optical Engineering, Vol. 5719, no. 1, pp. 14-22, December 2005.

[60] Basha, M.A., Dechev, N., Safavi-Naeini, S., and Chaudhuri, S.K., "A scalable

1×N optical MEMS switch architecture utilizing a microassembled rotating micromirror," IEEE Journal of Selected Topics in Quantum Electronics, Vol. 13, no. 2, pp. 336-346, March-April 2007.

[61] J. Carter, A. Cowen, B. Hardy, R. Mahadevan, M. Stonefield, and S. Wilcenski,

“PolyMUMPs design handbook,” MEMSCAP Inc.

[62] C. Bai, Scanning tunneling microscopy and its applications, Springer, 2000.

[63] A. Cowen, G. Hames, D. Monk, S. Wilcenski, and B. Hardy, “SOIMUMPs design handbook,” MEMSCAP Inc.

[64] LMC6001 Datasheet, National semiconductor, December 2003.

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