Optical-guided Autonomous Docking Method

for Underwater Reconfigurable Robot

Donny Sutantyo, David Buntoro, and Paul Levi

Institute of Parallel and Distributed System

University of Stuttgart

Stuttgart, Germany

Email: sutantdy@ipvs.uni-stuttgart.de

buntoro.david@gmail.com

levi@ipvs.uni-stuttgart.de

Abstract-This paper introduces the application of blue light sensor for guiding an individual AUV to dock to another one in clear water environment. Thanks to this method, an underwater reconfigurable robot can evolve from swarm mode into organism mode to perform other embodiment and locomotion mechanisms. Compared to classical sonar systems, the advantage of using blue light is the robustness to the multi robot interferences, the compactness of the hardware system, and the capability to ensure a high bandwidth communication. This ultimately enable the integration into miniaturized and low cost underwater swarm robotic platform. Experiments validate the proposed docking procedure demonstrating the working principles of the selected docking method and sensory system that work at an inter-robot initial distance up to five times the robot body-length (lOOcm).

I. INTRODUCTION

Unmanned underwater exploration is beneficial in fields

such as: pollution monitoring, offshore mining, general

oceanographic data collection, and marine biological obser­

vation.

Due to the very large extension of underwater environments,

the use of multiple autonomous robots is required to improve

the performance of exploration mission. For example, during

swarm operations, a team of AUVs can cooperate by balanc­

ing/sharing tasks in order to improve robustness and efficiency

to accomplish the mission. Furthermore, aggregation and re­

configuration capabilities can further improve the versatility of

the swarm enabling the possibility to generate whole robotic

entities with different morphologies adapted to specific tasks.

Therefore, mechanical reconfigurability is a promising features

in underwater robotics.

In swarm applications, reconfigurability can be achieved

by implementing docking capability among robots. In the

ANGELS EU project, several individual underwater robots,

which can move with propellers, are capable to aggregate and

to embody into whole entities composed of serially linked

robots that can perform anguilliform swimming [1] [2].

This case study indicates four major technological challenges

in the field of modular underwater robots: design of the

mechanical systems required for docking, underwater sensing

system for guiding the docking, an algorithm for performing

the autonomous docking mechanism, and an algorithm for

978-1-4673-6225-2/13/$31.00 ©2013 IEEE

Stefano Mintchev and Cesare Stefanini

The Biorobotic Institute

Scuola Superiore Sant' Anna

Pisa, Italy

Email: s.mintchev@sssup.it

cesare.stefanini@sssup.it

distributing and synchronizing anguilliform swimming gait. In

this paper we focus our work on the sensing technologies and

the mechanism for docking.

(a) (b)

Fig. 1. ANGELS robot (a) Single mode ; (b) Organism mode .

The paper is organized as follows. In Section II, the me­

chanical platform of the ANGELS robots and their docking

mechanism are described. In Section III, we discuss the blue

light sensing and communication system. Section IV describes

the experiments by using two methods. The last section,

Section V, is devoted to conclusion and future work.

II. ANGELS ROBOT AND DOCKING MECHANISM

The ANGELS robotic platform is composed of nine re­

configurable AUVs that can navigate autonomously as single

agents or can be serially connect together in chain morpholo­

gies composed of more than three AUV s that that are capable

of anguilliform swimming [1] [2]. The possibility to exploit

different morphologies aims at improving the versatility of

the system: a swarm of single agents can effectively spread

to investigate the environment, while the AUVs serially con­

nected can cover long distances by exploiting an energetically

efficient undulatory swim. To the best of the authors knowl­

edge, AMOUR [3] is the only other underwater robotic system

capable to autonomously reconfigure by vertically stacking

and unstacking functionally different modules (e.g. batteries,

propellers, buoyancy mechanisms and sensors).

Fig. 2 is the picture of the ANGELS final prototype and

its main systems. The two detailed sections show the internal

mechanisms of the docking system. The robot is composed of

Fig. 2. Picture of the ANGELS final prototype and its main systems. The two detailed sections show the internal mechanisms of the docking system.

a polymeric shell housing all the mechatronic and electronic

systems. The frontal and longitudinal sections of the shell have

a quasi-elliptic shape in order to minimize drag forces. The

dimensions of each AUV are 250 x 120 x 65 mm with a

neutral weight of l.2 Kg. Three miniature propellers and a

buoyancy system allow to control the 3D movements of the

AUV in water. Two (top and down) longitudinal propellers (PI

and P2) allow controlling forward, backward (surge) and pitch

motions, while a transversal propeller (P3) allows to steer the

robot (yaw). The roll degree of freedom is passively stabilized

thanks to a tailored distribution of weights inside the module.

The buoyancy system works in closed loop with a pressure

sensor in order to maintain the robot at a fixed depth during

docking.

The AUV can be serially connected thanks to a dedicated

hybrid docking mechanism composed of a magnetic alignment

system and a mechanical docking connection. The proposed

docking system exploits the interaction of permanent magnets

to passively align the AUVs when they are close to each

other (average distance of half body length). The magnets

work in synergy with the docking algorithms that actively

control the trajectory of the AUVs in order to provide the

alignment precision that is required by the mechanical system

to effectively dock the robots together. Furthermore, this

approach helps to partially compensate for the underactuation

of the AUV and reduces the overall alignment precision that

the docking algorithms need to ensure.

As shown in Fig. 2, the alignment system is composed of

two neodymium magnets placed in the stern (a) and the bow

(b) of the AUV. A DC motor (c) modifies the orientation of

the rear magnet generating the attraction or repulsion between

AUVs in order to respectively facilitate the connection and the

undocking.

The mechanical docking system relies on two screws placed

at the bottom and lower part of the stern. These screws (d1 and d2) penetrate into two movable links (jl and j2) equipped

with bolts that are placed in the bow of the AUV. Each

screw is actuated by a single DC motor (e) that produces the

torque required to tighten up the AUVs during the connection.

The motion is transmitted from the DC motor to an internal

shaft (f) by means of a couple of bevel gears (g). The shaft

is supported by means of two lubricated brass bearings. A

custom miniature magnetic coupling (h) allows transmitting

the torque from the internal shaft to the screw. The magnetic

coupling is composed of two paired magnetic parts separated

by a thin septum of polymeric material. This design allows

to completely seal the shell since the transmission of the

torque takes place contactless. The screws are equipped with

a custom axial bearing (i) in order to reduce the stick slip­

effect during unscrewing. The two connectors (jl and j2) in

the bow of the AUV are equipped with axially compliant bolts

(k) in order to compensate for possible misalignment between

AUVs, thus preventing the failure of the screwing process.

The compliancy it generated by two facing magnets (1) with

opposite magnetization. The lower link (j2) is connected to a

brushless motor to activate the undulatory movement required

to swim.

Fig. 3. Frontal and rear view of the ANGELS AUY. The robot is equipped with two blue light systems in the stern and the bow to guide the AUV during docking.

The connection between the AUVs is achieved in three

consecutive steps: I) an active approach of one AUV towards

another one using dedicated control algorithms that are able

to drive the propellers using the feedback of a blue light

sensory system. As shown in Fig. 3, the sensors are placed

both in the AUV stern and bow and are composed of two

receivers (m) and one emitter (n) . The docking algorithms

and sensors are presented in detail in the next sections; II) a

fine alignment step, when the robots are at a short distance

(approximately 50 mm), facilitated by the passive orientation

provided by the penn anent magnets; III) a final mechanical

connection to tightly dock together the two AUV. In smmnary,

in the proposed hybrid docking system, small permanent

magnets provide the required alignment precision enabling the

mechanical connection, while the screws provides the forces

required to dock together the AUVs.

Mainboard

Power Management

Board

Fig. 4. ANGELS electronic structure

III. SENSING AND COMMUNICATION FOR UNDERWATER

DOCKING SYSTEM

There are several major requirements and constrains re­

lated to sensing and conununication for underwater robotic

swarm [5] [6]. For example, multi-robot cooperation requires

the robot to be able to sense and to cOlmnunicate with 3D

omnidirectional patterns, thus each robot is always capable

to communicate with each other globally (global communica­

tion) or locally (local conununication) if they are at a short

distance. Directional cOlmnunication, distance sensing, depth

and orientation measurements are also required by the robot

in order to estimate the position of other robots, obstacles,

or its own position when it is performing localization in the

underwater environment. Since the effectiveness of swarm

operations relies on communication for concurrently percep­

tion, task balances and sharing among several AUV s, all of

the sensing and communication equipment must be robust in

order to cope with possible interferences. Furthermore, since

experimental swarm robot platform must be small, cheap, and

has low power consumption[6], the sensing and cOlmnunica­

tion peripheral are also crucial to meet these requirements.

Finally, if the underwater multi-robot system is endowed with

the capability to reconfigure, the sensing and communication

system has a strategic role since it enables the capabilities

to guide the robots according to dedicated docking algorithm

and to provide online communication among robots after the

embodiment process.

In this paper, blue light system is selected as the main part

for the sensing and communication architectures. The choice

of using optical system is due to its capability to be mod­

ulated/encoded and due to its directional pattern. Therefore,

it is feasible to use this single system both for directional

communication and sensing, thus reducing the space that is

required by the hardware. The features of many ready-made

optical modulators and encoders also made them possible to

be used in multi-channel cOlmnunication system for swarm

application. Blue light color is chosen, because blue is the less

absorbed light color in underwater application[5]. Later it will

also be described, how the blue light system is capable in mea­

suring gradient of the light for guiding the docking process.

Additionally, the high bandwidth of the optical cOlmnunication

system also enables online communication (e.g. to synchronize

the undulatory movements of the robots during the anguil­

liform swimming) among robots after the docking process,

when they are serially connected into a serial morphology.

Furthermore, 3D compass, 3D accelerometer, pressure sensor,

and RF communication are also installed in the ANGELS

robot for estimating the orientation, swimming depth, and

for local omnidirectional communication. It is important to

note that the compass measurement must be executed when

all motors, as noisy magnetic devices, deactivated for short

period.

The blue light system consists of two parts, the digital

modulated blue light and the analog blue light. The dig­

ital blue light is encoded and modulated signal intended

for packet based communication purpose. The analog blue

light is an ADC based light sensor that is used to measure

the gradient of the blue light intensity underwater in close

distance. A one chip conunercial solution by using CS 8130

IrDA chip from Cirrus Logic is selected. The IrDA chip has

programmable modulator, amplifier, signal conditioner, and

protocol encoder/decoder [12].

Blue Light Communication & SenSing

I BI�lID I (ChanneIA.1)

� I BIlK'LED �Iodulated SIgnal IrDA Controller

(<llanrwl A.2) CS8130

I . D.U. "ooDI""'''",,1

(Channel A) Sensith'e

��I

I B��:' r Analog Un-moduiatedSigqal

O>annol) Amplifier

Fig. 5. Blue light system

The table I shows our underwater measurement results that

compares the common encoded IR and blue light communica­

tion in 119 kbps of bitrate with several different of modulation

types [12] . It is shown that the blue light color outperfonn

the COlmnon infra red system, due to its behavior that is less

absorbed underwater, compare to the infra red spectrum.

Modulation Transducer Maximum Communication/Sensing IrDA Infra-red 7 em / 0-5 em

TV Remote Infra-red 5 em / 0-5 em QAM Infra-red 12 em / 0-5 em direct Blue LED 20 em / - / -lrDA Blue LED 60 em / 0-5 em

TV Remote Blue LED 45 em / 3-8 em QAM Blue LED 120 em / 7-12 em

TABLE I UNDERWATER OPTICAL COMMUNICATION MEASUREMENT (AT 1 19KBPS).

The internal programmable amplifier inside the IrDA chip

can also be used to measure the signal strength of blue-

� bgHtM'"'. StlnrtmtJa01FC �7.s..s.rtmlJ��4 '00

M..",tmum CommunicOIlion O'st.,nce

(em) vs Current Sensitivity (nA)

Fig. 6. Method for measuring signal strength by varrying receiver sensitivity.

light source. The chip has a re-configurable amplifier with 32

levels of attenuation to change the sensitivity of the receiver.

When the sensitivity threshold is set to minimum, it is able

to detect signal at the farthest distance. Inversely, it can only

detect signal at the shortest distance when the threshold is set

to maximum. Hence, by manipulating the sensitivity register

online, it is possible to make an algorithm for calculating the

gradient of the blue-light signal while performing inter-robot

communication.

According to the measurement results in Table I, both

for communication and sensing, the Quadrature Amplitude

Modulation (QAM) has been identified as the best modulation

for underwater application. Fig. 6 shows the relation between

current sensitivity value of the internal programmable ampli­

fier and maximum communication distance between robots.

By using this curve, an active sensing algorithm can be added

in the inter-robot communication algorithm. The robot can

estimate the relative distance with other robot by varying the

sensitivity of the amplifier via software.

Since encoded blue-light measurement has more non-linear

behavior in close distance (see Fig. 6 ), an amplified analog

signal from the blue light photodiode is added to the internal

LO-bit Analog to Digital Converter (ADC) to measure the

availability of high intensity blue light which occurs only when

the emitter and the sensor of two robots are close each other.

Therefore, by fusing both information from the ADC and

the IrDA chip, the uncertainty in measuring distance between

robots is reduced, because the functionality of the encoded

blue light in the non-linear area is replaced by the analog blue

light.

IV. EXPERIMENTS

The algorithm developed for guiding the docking is based

on the master-slave approach. The robot with the master status,

which is selected for robot with lower ID number, is kept in

a fixed position. The master robot transmits blue-light signals

to the slave robot during the whole docking procedure. If the

slave detects the signal, then it follows the optical gradient to

the location of the master. While performing the autonomous

docking, the slave must recognize the current orientation of

the master in order to effectively approach it. To do this, the

slave is guided by the signal that is continuously transmitted

by the master robot. In addition, each robot is equipped with

on-board magnetic compass as the feedback for the rotational

movement.

After being deployed underwater, the slave robot scans the

environment to find the signal source from the master robot by

performing random walk. As soon as the robot detects signal

from the master, it first synchronizes the swimming depth by

exchanging the pressure sensor measurement and actuating the

buoyancy system. To simplify the docking procedure and the

diving control algorithm, the robots are synchronized to move

at the water surface (2D docking).

Fig. 7. State machine of the robot controller

During random walk phase, the robot uses optimized

bio-inspired Levy flight random walk for determining the

swimming pattern. By using this method, the length of the

trajectory, before rotating to the other random direction, is

randomized by using Levy probability distribution function.

This bio-inspired random motion is concluded by biologist as

the optimized random search algorithm used by many species

for foraging activity [7] [8] [9].

Besides moving randomly, the robot is also transmitting

its own blue-light signal data and monitoring the availability

and intensity of the received blue-light signal. Collision with

obstacles and other robots are detected from differentiating

received address in the blue light data packet. If the robot

detects blue-light signal from another robot, it changes the

current state into docking state. The idea is to make the robot

approaching the master robot until it reaches the magnetic

region of the docking system.

(a) (b)

..... LatW'isb COmpleted

Fig. 8. (a) State docking; (b) Finding angle for best signal .

Fig. 8 and Fig. 9 illustrate the basic idea of the method.

When highest light intensity is detected, the robot is supposed

to be in the correct heading. Then it moves forward for n

second. If the robot somehow looses of the digital blue-light

signal, then it tries to obtain the signal again by rotating 360

degrees for scanning its surrounding area. Nevertheless, if the

robot fails to dock then it goes back to the random walk state.

A. Using encoded blue-light and digital compass for guiding the docking

In order to detennine the direction of the highest blue

light intensity, the robot uses the digital compass to mea­

sure the heading and creates a look-up table, which is the

function between the signal strength and the heading. In

the measurement table, the 360 degree complete rotation is

divided into 14 sections, with 25 degrees for each section.

The selected number for dividing the angle is chosen based

on the sensitivity of the compass.

Fig. 9. Docking method by using Encoded Blue-light and Digital Compass

The algorithm starts when the robot detects other robot blue­

light. Robot samples the magnitude of the signal while rotating

up to four sections by using inclining/declining principle. After

the sampling period is ended, the robot rotates to the section

with the strongest signal. Then, it moves forward for four

second. The algorithm repeats again by finding the best signal

location. One cycle of algorithm to find the best signal location

takes 30-60 second. This is due to the fact that the motor must

be turned off when digital compass is used.

During the experiment, robot manages to come closer to the

blue-light source, but unable to reach the master. The robot

managed to find the location of blue-light only when it is far

from the source. This problem is due to the characteristic of

the encoded blue light that has bigger non-linearity at close

distance (less than 20cm, according to Fig. 6) . The inability

to measure the gradient precisely at close distances and the

slow response of distance measurement algorithm causes the

robot to stop deciding the movements and makes its inertia to

drift out from the blue light region.

B. Using encoded blue-light, Analog blue-light, and Compass for guiding the docking

According to the Fig. 6, when the robot is close enough to

the blue-light source, calculating signal strength using CS8130

is more difficult. Instead, analog blue light measurement by

using ADC is used, because it takes less time to determine

the signal strength and has better response in close distance,

although it does not work in far distance due to the un-filtered

noise. The robot switchs the measurement to the analog blue

light system when the blue-light signal measurement estima­

tion from the CS8130 is lower than 20cm. State Approaching

Fig. 10. Drifting problem during docking

Target is introduced here so that robot can move closer to the

master by using the analog measurement.

Fig. 11. Robot controller after accomodating analog blue light

...tun> B.stStgua1Loc"uoDAe�d

(",.luWog "" d .. lIniDg "" (C'W'T'el1t_v.t>-best_val» II tun.out_o«u.r.d

Fig. 12. State Approaching Target

One example of experiment is illustrated at Fig. 13. Robot

scans the surrounding light (a-c), but somehow achieved

rotational drift (d) . From that drifted position, it performs

counter rotation and gets the signal back (e-f). Robot stores the

measurement on the look-up table, but achieved another drift

(g) . Robot corrects its heading direction, start the inclining­

declining method from here, while sampling the signal value

to the look-up table while rotating (h-i), The algorithm de­

tennines that heading (j) has the biggest signal strength, and

(m) (n) (0)

Fig. 13. The top view of the autonomous docking experiment with the ANGELS robot. The arrow indicates the position and the heading of the robot

re-scan by rotating four section to find the particular angle

(k) . Then the robot starts to approach the target (l-n). From

there, the signal from ADC measurement reach the threshold,

and the robot keeps moving forward, complete the docking

process by entering the magnetic region (0).

Initial Distance 40cm 60cm 80cm

> 100cm

Success Rate 73% 65% 45% 15%

TABLE II EXPERIMENTAL RESULT.

V. CONCLUSION

For miniature underwater reconfigurable robotic system, a

small and low power sensor system able to measure gradient

for guiding the autonomous docking is required. Blue light

system could be built small enough for the requirements.

Apart from size and power requirement, the blue light sys­

tem can also be used both for sensing and conununication.

Therefore, during the docking process, the guiding sensor is

able to estimate the relative position between two robots by

measuring the gradient of the light and by reading the compass

value while communicating information for synchronizing the

desired position at the same time. However, since the encoded

blue light system has non-linearity behavior in measuring short

distance, an analog circuit for detecting close range blue light

signal is added to improve the docking success rate.

According to the experimental result with ANGELS robot,

by combining the blue light system and the compass, it is

possible to create an autonomous docking method that can

work at a inter-robot distance up to five times the robot body­

length (total distance of 100 cm). The addition of the analog

blue light circuit for measuring gradient at low distance « 20

cm) improves the performance of the docking process.

For future work, combining the optical system with the other

sensing system (i.e. electric sensor in ANGELS robot [14]) are

necessary to further improve the success rate of the docking

algorithm.

ACKNOWLEDG MENT

This work is supported by the ANGELS European Union

project. Project Reference: 231845; Seventh Frame Program,

research area: ICT-2007.8.5-FET Embodied intelligence.

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