1028:PICARSOSven Paschburg2 System Process Design Problems Design Specifications Hardware Painting...

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1028:PICARSO

Ian HOOI

Samuel OOSTERHOLT

Sven PASCHBURG

Joyce PHAN

Neil YEOH

Supervisor: A/Prof Ben CAZZOLATO

PROGRAMMABLE INTERFACE CONTROLLER WITH

AUTONOMOUS ROBOTIC SPRAYING OPERATION

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Seminar Outline

System Process

Design Problems

Design Specifications

Hardware

Painting System

Image Processing

Control Software

Testing and Results

Project Outcomes

Future Work

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System Process

Hardware Painting System

Image Processing

Control Software

PICARSO:Cable-driven robotProcess standard image formatsReproduce images on vertical surface

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Processed

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Design Problems

Image Output

End-Effector

Original Painted

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Design Specifications

Cables

End-Effector

Motor 1

Motor 2Motor 3

Vertical Wall

CablesImage Processing Toolbox RS232

Graphical User Interface Design Environment(GUIDE)

(Mathworks 2010)

MATLAB

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Hardware

Design Problem

Design Specifications

System Architecture

Hardware

Painting System

Image Processing

Control Software

Testing and Results

Project Outcomes

Future Work

Samuel Oosterholt 7

Hardware Goals

Goals: Develop mechanical system

Scalable work space sizeUp to 3×3m

Manipulate and stabilise the end-effectorMounting the system:

in operation andin testing

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Hardware: Previous Work

Image producing robots Scalable workspace size

Cable driven

Hektor (Franke & Lehni 2002) Viktor (Lehni & Rich 2008)

Hektor’s actuator configuration

Viktor’s actuator configuration

PICARSO’s actuator configuration

Two actuators ‘V’ Configuration Relies on gravity

Four actuators ‘X’ Configuration

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Mechanical System

Three motors

‘Y’ configuration

Cables

Upper motors control position

Lower stabilises Reduces cost

Full System

Render of PICARSO system

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Mechanical System

Base Plate

Motor

Motor Controller

Spooling System

Cable feeding system

Motor Mount

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Mechanical System

Motor Mount

Motors parallel to painting surface

Plate mounts to painting surface

Double spool and bearing

Two cables Reduce yaw

and pitch Minimise

kickback

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Cables: Spiderwire (Braid

fishing line) Ø = 0.30mm Tmax = 13.6kg Small elasticity

10m of cable 7×7m workspace

Cables attach to turnbuckles

Reorientated by eyebolts and pulleys

Can move pulleys and eyebolts Proximity to canvas Stability

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Mechanical System

180°Motor Mount

Lower mount uses fairleads 180° sweep

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Drive System Hardware Specifications

Hardware selected from Maxon MotorsNumerous operation

modesModular componentsDiscounted cost & support

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250W EC45 Motors and Maxon EPOS2

70/10 Motor Controller

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Mounting for Testing

Canvas implementedSimulate surfaceReduces ripple in wind

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PICARSO’s easel in the Vibrations Laboratory

PICARSO’s easel in the FSAE shed

PICARSO’s canvas

Not feasible to wall mount for testing 3.6 × 3.2m easel (working area: 2.8 × 2.8m) Constrained by testing environment

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Painting System

Design Problem

Design Specifications

System Architecture

Hardware

Painting System

Image Processing

Control Software

Testing and Results

Project Outcomes

Future Work

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Painting System Goals

Goals: Design an appropriate painting system

which: Produces circular patterns (< 3cm) Is fast (> 1Hz) and light (< 3kg) Does not cause instabilities Houses suitable paint capacity Is reliable, durable, and repeatable

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Circular Patterns ( <3cm)

Fast ( >1Hz)

Light ( <3kg)

No Instabilities

Paint Capacity

Reliable

Durable

Repeatable

Spray Can Airbrush Spray Gun*1 *2 *3

Painting Mechanisms

Three types of painting mechanisms

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** Image references at end of slides

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Spray System Schematic

Paint Line

Air Line

Electrical Signal

Compressed Air Line

Electrical Air Compressor

Air Regulator

Automatic Pressure-fedSpray Gun

Personal Computer

SolenoidPressurised

Paint Canister

Paint Regulator

*4

*5

*6

*8

*7

*9

** Image references at end of slides

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Spray Gun Choice

Anest IwataSGA-101 Automatic Pressure-fed Spray Gun

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Fluid Adjust Knob

Fitting Knob

Paint Line

Pattern Adjust Knob

Air Line

Nozzle

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Spray Gun Settings

Testing procedure Ideal Settings identified:

Results:Consistent < 3cm black circles

Specification Setting

Air Pressure 2.0 bar

Paint Pressure 0.5 – 1.0 bar

Spray Distance 5 – 10 cm

Fluid Adjust Knob Half Turn

Spray Duration 0.2 – 1.0 s

Spray Duration

Rep

eata

bilit

y

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Painting System: Spray Gun Housing

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Spray Gun Housing

Small Sleeve

Large Sleeve

BearingsEyebolts

Sleeve Shaft

Bearing Spacer

Spray Gun

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Spray Gun Housing

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Image Processing

Design Problem

Design Specifications

System Architecture

Hardware

Painting System

Image Processing

Control Software

Testing and Results

Project Outcomes

Future Work

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Image Processing Goals

Goals: Develop image processing software to:

Transform input image to user specified settings

Reproduce input image in binary formOutput in Raster (pixel-by-pixel) form

Extension Goal:Output in Vector (line) form

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Image Transformations Procedure

1. Input image

2. Resized to appropriate resolution

3. Stretching and refitting

4. Greyscale formScaled from 0-1 where 0 is black, 1 is white

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Resized GreyscaleOriginal

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Fill and Edge Binary Images

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Fill Image Edge Image

Fill Images: Direct conversion from greyscale binary

Edge Images: outlines of the image

Fill Image Edge Image

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Binary Image Threshold Settings

Converted to binary formThreshold filter

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Original Binary: Threshold = 0.25

Binary: Threshold = 0.5 Binary: Threshold = 0.75

Original Binary: Threshold = 0.25

Binary: Threshold = 0.5 Binary: Threshold = 0.75

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Output Type: Raster vs. Vector

Raster: pixel by pixel approach Vector: line based approach

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10 20 30 40 50 60

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Optimal

Raster Based Output

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Vector Based Output

10 20 30 40 50 60

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Optimal

Raster Based Output

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Vector Based Output

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Raster Based Approach

Image output in binary form1 represents white0 represents black

Read and processed by Control Software Slow to paint

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1020

3040

5060

20 30 40 50 60 70

Optim

al

1020

3040

5060

20 25 30 35 40 45 50 55 60 65 70

=

0 1 1 1 0

1 0 1 0 1

1 1 0 1 1

1 1 0 1 1

1 0 0 0 1

0 0 0 1 1

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Vector Based Approach

Aim: Raster Vector Searching Algorithm based on Portrayer

(Benedettelli 2008) and Erik’s XY Plotter (2007)

Adjacent pixels chains Control software

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=10 20 30 40 50 60

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50

60

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Optimal

10 20 30 40 50 60

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Control Software

Design Problem

Design Specifications

System Architecture

Hardware

Painting System

Image Processing

Control Software

Testing and Results

Project Outcomes

Future Work

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Control Software Goals

Goals: Software for Raster Mode

Convert Image Processing output to:• Control motors• Control spray gun

Extension Goals: Software for Vector Mode Graphical User Interface (GUI)

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Control Software Flow Diagram

ImageProcessing

Output

Inverse Kinematics

Motor Commands

CableLengths

PositioningCommands

CartesianCo-ordinates

Spray Gun Commands

xy

L1 , L2 , L3

1 0 0 1

on off

turns

Motor Turn Units

ControlSoftware

OutputCommands

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Vector Mode

Positioning Commands

0 1 1 1 0

1 0 1 0 1

1 1 0 1 1

1 1 0 1 1

1 0 0 0 1

0 0 0 1 1

Image ProcessingOutput

Raster Mode

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Inverse Kinematics

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Communication

PC Master

SolenoidRS232

Digital Output

RS232

RS232

Motor Controller 1 Slave

Motor Controller 2 SlaveMotor Controller 3 Slave

• Instructions from Master to Slaves via 3 Parallel RS232 links

• Outputs controlled in Maxon RS232 Communication Protocol

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Motor Operation Modes

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Motor 3 Motor 2

Motor 1

Position Mode Position Mode

Current Mode

• Position Mode• Driven in steps

• Current Mode• Provides tension• Minimises instabilities

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Click icon to add picture

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Graphical User Interface (GUI)

• Easy access to user settings during operation

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Testing and Results

Design Problem

Design Specifications

System Architecture

Hardware

Painting System

Image Processing

Control Software

Testing and

Results

Project Outcomes

Future Work

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Testing and Results

Goals: Scaled system – µAngelo Full scale system – PICARSO Image processing software Control software Graphical User Interface (GUI)

Extension Goals: Vector-based painting Touch screen interface

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Testing and Results

Kinematics test bedTri-motor Y-configuration proof of concept

Scaled System - µAngelo

Oblique angle picture of µAngelo

Front view picture of µAngelo

Picture of µAngelo’send-effector

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Testing and Results

Raster painting functionalityScalable across a vertical surface

• Up to 3×3m workspace areaComplete a picture in 1 hour

Full Scale System - PICARSO

Accuracy & PrecisionReliabilityWorkspace Resolution

Pixel SizeStabilitySpeed

Test Metrics

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100 mm

50 mm10 mm

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Testing and ResultsRaster Painting Functionality

Specifications Achievement

Accuracy ± 10 mm

Precision ± 5 mm

Workspace Resolution

10 – 100 mm

Workspace Resolution (ideal)

10 – 25 mm

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Testing and Results

Parameter Achievement

Pixel Size (min.) 8 mm

Pixel Size (ideal) 10 mm

Raster Painting Functionality

0.2 s 0.25 s 0.5 s 1.0 s

8 mm 10 mm 16 mm 20 mm

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Testing and Results

Specifications Achievement

Stability ± 25 mm (z – axis)

Raster Painting Functionality

x

z

y

Side view of the end-effector

Bottom view of the end-effectoryaw

pitch

roll

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Testing and ResultsScalable across a vertical surface

Specifications Achievement

Workspace Area 0.5 × 0.5 m to7.0 × 7.0 m

A picture showing the ability of the end-effector to move around the workspace

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Goals: Scaled system – µAngelo Full scale system – PICARSO Image processing software Control software Graphical User Interface (GUI)

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Project Outcomes

A 1.8 × 1.8m painted ‘fills’ image of the Mona Lisa

Oblique angle picture of µAngelo

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Future Work

Extension Goals: Analog communication Complete a picture in 1 hour Vector-based painting Touch screen interface

Future years: Colour painting Wireless communication Commercial product

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Questions and Comments?

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References

Benedettelli, D. 2008, NXT Portrayer Robot, viewed 11th April 2010 <http://robotics.benedettelli.com/portrayer.htm>

Convict Episcopal de Luxembourg, 2007, Erik’s XY-Plotter, viewed 11th April 2010, <http://www.convict.lu/Jeunes/ultimate_stuff/Erik_s_xx_plotter/E_xy_plotter.htm>.

Franke, U & Lehni, J 2002, Hektor, viewed 29 December 2009, <http://www.hektor.ch/Book/Hektor.pdf/>.

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Painting System References

1. Spray can - http://comps.fotosearch.com/comp/UNN/UNN113/spray-can_~u14072509.jpg

2. Airbrush - http://imgs.tootoo.com/e1/00/e10006f419523aa3bb036a77fb5038dd.jpg

3. Spray gun - http://image.made-in-china.com/2f0j00DaTQeBfgIEMJ/HVLP-Spray-Gun-RP8021-2S-H827-S-.jpg

4. Air Compressor - http://toolmonger.com/wp-content/uploads/2006/05/aircompressor.jpg

5. Festo Air Regulator - http://www.festo.com/rep/nl-be_be/assets/LR_2008_1314u.jpg

6. Pressurised Paint Canister - http://www.smitsgroup.co.nz/images/objectimages/PT2-Paint-Tank.jpg

7. Festo Solenoid Valve - http://www.luconda.com/artikeldetails/27/29/xx/bilder/2093457-1-Festo-CPE18-M1H-3GL-1-4.jpg

8. Iwata Spray Gun - http://www.anest-iwata.co.jp/english/products/paint/prd/fog/auto/images/ceramic_ph01.jpg

9. Personal Computer - http://www.ubergizmo.com/photos/2008/12/dell-xps-13.jpg

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Further Examples and Information

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Hardware

HardwarePainting System

Image Processing

Control Software

PICARSO

Mechanical &Electrical

Software

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End-Effector

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Higher Level Software Flow Diagram

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Raster Functionality

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Vector Functionality

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Vector Algorithm Demonstration

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PICARSO Analog Communication

PC MasterEPOS2 Slave (Node 1)

EPOS2 Slave (Node 2)

EPOS2 Slave (Node 3)

NI PCI-6221 card(Analogue Inputs)

NI SB 68-LPBreakout Board

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Click icon to add picture

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Control Software: Main Menu GUI

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Click icon to add picture

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Control Software: Paint Raster Image GUI

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Click icon to add picture

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Control Software: Paint Vector Image GUI

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100mm Pixel Spacing

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50mm Pixel Spacing

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25 mm Pixel Spacing

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10 mm Pixel Spacings

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Testing and Results

Raster processing functionalityProcess an image in less than 60sVector processing functionality

Image Processing Software

Processing Settings Options

Image Input JPEG, PNG, GIF, BMP, TIFF

Image Resolution 10 – 500 pixels

Image Threshold 0 – 1

Conversion Type Fills, Edges

Palette Type Binary (Black & White)

Sizing Square, Original Aspect Ratio

Image Processing Time < 3 s

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Testing and Results

Raster functionalityHuman Machine Interface (HMI)Vector functionalityTouch screen interface

High Level Control Software

Specifications Options

Control Mode Raster Painting, Vector Painting, Manual Positioning, Spray Control

Platform Mathworks MATLAB 2007 +

Operating System Windows XP, Vista, 7

Interface Type Graphical (Touch Screen)

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Testing and Results

Position the motorsControl the motor velocity and accelerationRead back the current positionActuate the spray gun solenoid

Low Level Control Software

Specifications Options

Control Functions Position Control, Set Max. Velocity & Acceleration, Read Current Position, Activate Digital Output

Platform Mathworks MATLAB 2007 +

Operating System Windows XP, Vista, 7

Positioning Accuracy (theoretical) 2.11 × 10-3 mm

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Testing and ResultsComplete a picture in 1 hour

Parameter Specification

Speed 2 – 250 mms-1

Acceleration 2 – 150 mms-2

Picture Time (av.) 2.5 hrs (edge image)

A 1.8 × 1.8m painted ‘fills’ image of the Mona Lisa

A 1 × 1m painted ‘edge’ image of the University of Adelaide logo