Modelling and control of bioinspired robotic fish underwater vehicle and its propulsion mechanism

30 1.6.1 Dynamics modeling of the robotic fish based on biology inspired principle.. 69 3 Kinematic Modeling of the Robotic Fish based on Lighthill’s Slender Body Theory 71 3.1 Introduct

Fish Underwater Vehicle and its Propulsion

Mechanism

ABHRA ROY CHOWDHURY

(M.Tech., Indian Institute of Technology B.H.U., Varanasi India)

A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF ELECTRICAL AND COMPUTER

ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE

2014

I hereby declare that this thesis is my original work and it has

been written by me in its entirety I have duly acknowledged all

the sources of information which have been used in the thesis.

This thesis has also not been submitted for any degree in any

university previously.

NAMtr: Abhra Roy Chowdhury

DATtr: 16 lL2 12074

I take this opportunity to infinitely thank my supervisor, Assoc Prof Dr.Sanjib Kumar Panda, by including me as a PhD student in his esteemed Elec-tric Machines and Drives (EMDL) research group He has reposed tremen-dous faith in me and always encouraged by letting me explore my own ideas.

He has been extremely kind, considerate and supportive for the entirety of mythesis work Moreover, he gave me the opportunity to go to many conferencesand workshops as well as take an active part in the STARFISH2 project Healways took the time to promote my work during his presentations to the in-dustry and academia Furthermore, he is a wonderful human being to knowand to work with, being friendly and supportive even in his busy schedule Ihave learnt from him to be independent, inquisitive, open-minded and mostimportantly patient in research I admire him for many reasons but the mostimportant habit I have tried to inculcate from him is the positive attitudeand work-life balance

I would also like to immensely thank Dr Sangit Sasidhar for the greatcollaboration I had found with him for a main part of my thesis I wish toexpress my sincere gratitude to Mr Y C Woo, and Mr M Chandra ofElectrical Machines and Drives lab, NUS, for their constant and selfless sup-port Their continuous support have made a noticeable contribution towards

my research progress

I would like to thank Mr Alok Agrawal, Mr Vinoth Kumar, Mr

Bhuneshwar Prasad for their key contributions for the hardware ment of the project I would like to acknowledge useful suggestions andfeedback given by Dr Rajesh Kumar of MNIT Jaipur, Dr Wang Xue, Dr.Manasa Behera of Tropical Marine Science Institute (TMSI) NUS, Mr Shail-abh Suman of Acoustic Research Lab NUS, Assoc Prof Mandar Chitre ofAcoustic Research Lab NUS, Dr Pablo Alvaro Valdivia of Singapore-MITAlliance for Research and Technology (SMART), Assoc Professor Marcelo

develop-H Ang Jr., Professor Xu Jianxin and Assoc Professor Abdullah Al Mamun

of Department of Electrical and Computer Engineering I sincerely thank theoffice of Defense Science and Technology Agency (DSTA), under the Ministry

of Defense (Singapore) for their support of the present research

I wholeheartedly thank Dr Parikshit, Subhash, Saurabh, Dr Zhaoqin,

Dr Chinh, Tran, Jeevan, Jayantika, Kalpani, Amit, Sicong and all my leagues in Electrical Machine and Drives Laboratory for useful discussionsand assistances

col-Pursuing my research would not have been possible without a good circle

of friends around me in Singapore I wholeheartedly thank all of them for allthe great times during the period of my study It certainly helped me a lot

in these last four years

I would like to express all my gratitude to my parents Mrs Sati RoyChowdhury and Mr Smaran Roy Chowdhury for their unfailing support,unconditional love and unbound patience This thesis would not have beenpossible without them I would like to dedicate this thesis to my parents.Last but certainly not least, I would like to thank the Almighty for helping

me to learn innumerable life lessons and showing me the direction during thecourse of my research

Summary xi

1.1 Background 1

1.2 The STARFISH 2 Project 3

1.3 Fish Swimming Mode Classification 8

1.4 Related Work 12

1.5 Motivation and Problem Statement 20

1.5.1 Challenge 1: Bio-inspiration from Fish Swimming Modes for Underwater Vehicle Propulsion and Maneuvering 22 1.5.2 Challenge 2: Improvement of Energy Efficiency vis-a-vis the Capability of Propellers 23

1.5.3 Challenge 3: Stealth and Noise Signature left by AUVs 25

1.5.4 Challenge 4: Bio-inspired Control and Navigation

Sys-tem of Underwater Vehicles 26

1.5.5 Challenge 5: Learning from Group Behaviour and

Dis-tributed Senses of Aquatic Animals 28

1.6 Thesis Contributions 30

1.6.1 Dynamics modeling of the robotic fish based on biology

inspired principle 30

1.6.2 Kinematics modeling of the robotic fish and

mathemat-ical input waveform design under Lighthill framework 30

1.6.3 Hydrodynamic Modeling matched with Kinematics of

actual fish 31

1.6.4 Control Design Methodologies and Comparison 32

1.6.5 Behaviour based control architecture 32

1.7 Overview of the Thesis 33

2.1 Introduction 39

2.2 System Model 42

2.2.1 Robotic Fish (Anterior) Head 48

2.2.2 Robotic Fish (Posterior) 2-Link caudal tail as Thruster 50

2.2.2.1 Velocity and Acceleration vectors 51

2.2.2.2 Forces and Torques 52

2.2.2.3 Hydrodynamic Forces: Added Mass (Lighthill’s

Reactive Force) 52

2.2.2.4 Pressure Drag (Resistive) Force 63

2.2.2.5 Buoyancy Force 64

2.2.2.6 Control forces and Servo motor Dynamics 64

2.2.3 Equation of Motion in Earth-fixed Frame 65

2.3 Conclusion 69

3 Kinematic Modeling of the Robotic Fish based on Lighthill’s Slender Body Theory 71 3.1 Introduction 71

3.2 Lighthill0s Slender Body Theory based Mathematical Framework 75 3.2.1 Oscillating Sine with Linear Amplitude Wave 78

3.2.2 Undulatory Lighthill Quadratic Amplitude Body Wave 80 3.2.3 Undulatory Lighthill Cubic Amplitude Body Wave 81

3.2.4 Non-Uniform Rational B-spline (NURB) Quadratic and Cubic Body Wave (Tadpole-like Motion) 82

3.2.5 Undulatory SINC and DIRIC Body Wave 86

3.2.6 Undulatory Anguilliform Body Wave (EEL-like Ma-neuvering Model) 88

3.3 Lighthill Control Parameters 92

3.3.1 Tail Beat frequency (TBF) Based Control 93

3.3.2 Caudal Amplitude (CA) Based Control 96

3.3.3 Propulsive Wavelength (PW) and Propulsive Body-wave

Speed Effects 98

3.3.4 Yaw Angle effects 101

3.3.5 Determination of Lighthill’s Coefficients 105

3.4 Experimental Results and Discussions 106

3.5 Operating Region (ORE) 114

3.6 Conclusion 118

4 Hydrodynamics Modeling of the Robotic Fish 121 4.1 Introduction 121

4.2 CFD Modeling of Lighthill 0 s theory based Undulatory Motion 125 4.3 Simulation Results and Discussion 133

4.3.1 Pressure and Velocity Field Distributions 133

4.3.2 Tail-beat frequency (TBF) Effects 142

4.3.3 Caudal Amplitude (CA) Effects 145

4.4 Conclusion 149

5 Control System Design of the Robotic Fish 151 5.1 Introduction 151

5.2 Control Methodologies 155

5.2.1 Computed Torque Control Method with Dynamic PD compensation 157

5.2.2 Computed Feed-forward Control Method with Dynamic PD compensation 160

5.2.3 Computed Feed-forward plus Computed Torque Method 162

5.3 Experimental Results and Discussion 165

5.4 Conclusion 177

6 Behaviour Based Control Design of the Robotic Fish 181 6.1 Introduction 181

6.2 Kinematics based Brain Map and Control Architecture 190

6.2.1 Distance based Priority / Action Selection 192

6.2.2 Error based Priority / Action Selection 194

6.3 Kinematics Behaviour based High level Control 196

6.3.1 Tail Beat Frequency (TBF ) and Phase Shift 197

6.3.2 Caudal Amplitude (CA) Shift 198

6.3.3 Mixed Parameters Shift 199

6.4 Central Pattern Generator (CPG ) Model 201

6.5 Inverse Dynamics Based Low Level Control 204

6.6 Modulated Pattern Generators (MPG ) Model 212

6.6.0.1 Caudal Amplitude (CA) Parameter Modulation213 6.6.0.2 Tail-beat Frequency (TBF ) Parameter Mod-ulation 216

6.7 Conclusion 217

7 Conclusions and Future Works 221 7.1 Final Conclusions 221

7.2 Future Work 227

7.2.1 Sensory-inspiration of aquatic animals 227

7.2.2 Group behaviors of aquatic animals 228

The research objective is to understand how unmanned underwater cles (UUVs) running on the laws of physics can mimic fish biology principlesand deliver better locomotion Fishes have evolved for over 4.5 billion yearsleading to more than 32,000 species, exhibiting greater species diversity thanany other group of vertebrates [1] This makes them the front-running designchoice for this bio-inspired machine design The main focus is the locomotionpattern, energy efficiency and maneuverability of these species that can besuitably modified and translated to the vehicles performance improvement.The evolutionary process of fishes was studied [2], specifically their distinctclassifications and morphological traits The relation between these factorsand the fish locomotion pattern was observed in different fluid environments.Firstly, it was imminent to understand the internal and external body pa-rameters that can be translated to a fish inspired vehicle design The majorkinematic parameters of the robotic fish were chosen based on the kinemat-ics and energetics study of yellow fin tuna by experimental biologists Theseparameters were found to produce the undulating patterns in the spinal col-umn of the fish body with optimal thrust The major parameters were studiedbased on a yellow fin tuna comparable to the robotic fish scale The next stepwas to find a bio-fluid-dynamic equation that can accommodate these param-eters as well as be used as a plug-in body wave generator The answer wasfound with the Lighthills slender body theory This equation was integrated

vehi-to redefine the dynamics of the robotic fish vehi-to understand the kinematic lationship with different locomotion patterns The accuracies of hydrostaticand hydrodynamic forces were tested to understand the efficacy of the new

re-dynamic model in water Each hydrore-dynamic coefficient was validated rately against one of these kinematic parameters A novel dynamic model of

sepa-a robotic fish underwsepa-ater vehicle wsepa-as proposed by unifying conventionsepa-al rigidbody dynamics and bio-fluid-dynamics of a carangiform fish swimming given

by Lighthill’s (LH) slender body theory An inverse dynamic control methodbased on non-linear state function model including hydrodynamic parame-ters is proposed to improve the tracking performance Further, the dynamicmotion closed loop control strategies for the robotic fish were developed andcompared based on three different nonlinear control schemes These are CTM(Computed-Torque Method), FF (Computed Feed-Forward) controllers bothwith dynamic PD compensation and finally a proposed combination of CTMwith FF A Matsuoka based non-linear oscillator CPG structure is used togenerate the desired rhythmic pattern preserving control properties like sys-tem stability and synchronization A two level locomotion control architec-ture based on vertebrate fish biology is proposed, where a high level controllerplans the desired trajectory and the synchronization of these trajectories ateach joint, generates the fish-like locomotion behavior Subsequently, a lowerlevel control scheme uses an inverse dynamics model based policy for trackingthis locomotion pattern on the nodes along the spinal column of robotic fish

1.1 AUV and Bio-inspired AUV 5

1.2 Fish Swimming Modes Classification 10

1.3 Robo-Tuna II built in MIT 1994 with lever, pulley and ball bearing mechanisms 13

1.4 PPF-04 Uni-link robot fish design by NMRI, Japan 14

1.5 Robotic Fish Chinois SPC-03 developed in BUAA-CASIA China for underwater exploration 15

1.6 Robotic Eel Angulliform Fish (Robea Project) developed in CNRS France 16

1.7 Essex G8 Robotic Fish diving mode in water 17

1.8 Jessiko V4 Robotic Fish developed in France by RobotSwim 18 1.9 NTU Robotic Fish 20

2.1 Solidworks Robotic Fish Model 44

2.2 Relative orientations and locations of local coordinate frames at the CM of the head and the Inertial reference frame 46

2.3 BCF mode Carangiform swimming and travelling wave gener-ation 55

3.1 BCF mode carangiform 75

3.2 Block diagram showing integration of LH Model in the robotic fish kinematics and dynamics model 79

3.3 Undulatory Cardinal Sine travelling wave function 87

3.4 Power Spectral Density of Mathematical Waveforms 91

3.5 Forward Velocity vs Tail beat Frequency 95

3.6 Lighthill Amplitude Variation and Forward velocity (u)at dif-ferent values of envelope coefficients c1 and c2 96

3.7 Forward Velocity vs Amplitude at different wavelength values(Operating Region) 973.8 Forward Velocity vs Wavelength (Operating Region) at agiven TBF = 0.3 983.9 Propulsive Wavelength and Body Wave speed variations 1003.10 Yaw Angle vs Tail beat Frequency at different wavelengthvalues (Operating Region) 1013.11 Forward Velocity vs Yaw Angle 1023.12 Actual Robotic Fish Path under LH Cubic Undulatory Wave-function 1023.13 Light-Hill Implementation Envelope (Undulation) Formation 1063.14 Relative Path comparison relative to a Centre point (origin) 1073.15 Trajectory traversal between two fixed points using differentoscillatory/undulatory wave-functions 1113.16 Time Trajectory for different oscillatory/undulatory wave-functions112

3.17 Relative Path comparison between Tadpole-like, Carangiformand Anguilliform undulatory body waveforms 1143.18 Kinematic Experimental Results 1173.19 Closed-loop Hardware prototype motion in different frames 118

4.1 Mesh Structure and View of 2D Dynamic meshing for the threesegment robotic fish model 1294.2 Schematic diagram for undulation of fish tail at different timeinstants 1344.3 Pressure field and Velocity Field contour distribution aroundthe fish body 1354.4 Hydrodynamic coefficients Cd and Cl at different kinematicparameter values 1414.5 Hydrodynamic coefficient Cdvariation with Tail-beat frequency(TBF) parameter 1434.6 Hydrodynamic coefficient Cd variation with Amplitude Span(AS) parameter 1464.7 Forward Velocity at different kinematic parameter values inthe operating region 148

5.1 Computed-Torque Control (CTM) Model of Robotic fish 158

5.2 Feed-forward Control (FF) Model of Robotic fish 161

5.3 Feed-forward plus Computed Torque Control (FF) Model of Robotic fish 163

5.4 Trajectory Tracking using Inverse Dynamics based PID, CTM, FF and FFCT schemes 166

5.5 Actual Robotic Fish Path with LH cubic spline wave under CTM, FF and FFCT schemes 174

5.6 Closed-loop Hardware prototype motion in different frames 177

6.1 Carangiform Swimming Model showing undulation motion pat-tern in 1/3rd of posterior body generated by coupled motoneu-ron in mid-line 183

6.2 Behaviour architecture using DES model 191

6.3 Fish biology based Speed Profile of Robotic Fish 193

6.4 Stimuli based Action Selection 195

6.5 Block diagram of Brain-map modulated Behaviour Feedback based Control Scheme 196

6.6 Block diagram of Brain-map modulated Behaviour Feedback based Control Scheme 197

6.7 Kinematic Parameter Adaptation 200

6.8 CPG Signals and generated Trajectory Tracking using Inverse Dynamics based CTM scheme 208

6.9 Proposed Bio-inspired Distributed Control Dynamic Gains 211

6.10 Block diagram of Neurobiology inspired Distributed Control Scheme 213

6.11 MPG Signals and generated Trajectory Tracking using pro-posed Control structure 214

3.1 Trajectory (Geometric) Points for mathematical oscillatory/undulatorypropulsive waveforms 1083.2 Trajectory (Geometric) Points for mathematical oscillatory/undulatorypropulsive waveforms 108

Caudal AmplitudeComputational Fluid DynamicsCentre of Mass

Central Pattern GeneratorComputed Torque MethodDiscrete Event SystemsDenavit HartenbergElectroactive PolymersFeedforward

Combination of Feedforward and Computed TorqueFluid Structure Interaction

Finite State MachineLighthill

Median Pectoral FinModulated Pattern GeneratorNational Advisory Committee for AeronauticsNon Uniform Rational Bezier-spline

Operating RegionPerformance IndexPolypyrrole PolymerPower Spectral DensityPropulsive WavelengthStandard DeviationShape Memory AlloySmall Team of Autonomous Robotic FISHTail-beat Frequency

User Defined FunctionUnmanned Underwater Vehicle

Position of base frameVelocity of point wrt inertia frameVelocity of point wrt base frameInertia matrix (head) with added inertiaCoriolis-centripetal matrix

Gravity matrixPropulsion forces vectorPosition and orientation vector in earthfixed frameLinear and angular velocity vector bodyfixed frameTransformation matrix

Reaction ForceTorque

Generalized ForceLateral push of body-waveCaudal amplitude parameterTail-beat frequency

Lateral velocity

Forward velocity of the bodyFroude’s efficiency

Control points (vector)Drag Coefficient

Lift CoefficientTuned position gain matrixTuned velocity gain matrixExternal noise

System statesPhase angleSystem frequency responseCarrier body-wave signalModulating body-wave signalModulated body-wave signal

There is currently an increased interest in the use of long range/long durationUnmanned Underwater Vehicles (UUV’s) for oceanographic observation, mil-itary surveillance and commercial search missions Existing Autonomous Un-derwater Vehicles (AUVs) [1,2] are relatively small vehicles for three reasons:low cost (fully autonomous vehicles have a significant probability of beinglost), ease of deployment (to allow operations from conventional ships), andsafety (to minimize the danger to manned ships and installations) They arepowered by small rotary propellers driven by electric motors The propellerstypically operate at fairly low efficiencies and suffer from serious lag times

in transient response These problems lead to short mission times, restrictedpayloads, and control problems On the other hand, the fishes are found to

be highly maneuverable and effortless swimmers It has taken more than

160 million years to superbly adapt themselves to the watery environment

As society becomes ever more technologically advanced, electromechanical

systems are playing an increasingly important role in performing hazardoustasks; tasks that human otherwise could not perform, and even mundanetasks such as household chores Not only should robotic systems be able

to perform these tasks, but they should be able to do so as reliably and asrobustly as possible

One of the primary areas of focus for any robotic system is its means

of locomotion Recent advances in robotics have led to the development ofunderwater robot systems The state-of-the-art research work presents contri-butions to developing an underwater propulsion system through a bioinspireddesign process with a focus on a rather simple, yet efficient swimming mech-anism The problem of synthesizing the engineering approach for a highlybiologically inspired system for locomotion is addressed in liquid environ-ment by combining millions of years or evolution with modern engineeringknowledge The motivation and objective as well as the outline of the re-search work are provided in this chapter The field of robotics is undergo-ing rapid changes as technology continues to allow the development of evermore complex systems One of the fastest growing areas of development is

’Biomimetics’[3,4,5], in which robots are designed with the intention of icking nature However, mimicking natural systems presents an enormouschallenge to any designer as nature has had millions of years to develop thecomplex mechanisms present in the bodies of animals Take for example, thehuman arm From the shoulder to the wrist, it has 7 degrees of freedom

mim-To mimic such motion, traditional modern design would require a skeletalsystem of complex linkages, joints, hinges cables, pulleys and up to 7 dif-ferent actuators Even slightly more advanced designs, which may utilizeimprovements such as under-actuated system and the latest developments inactuation, would still require multiple parts and would require a high degree

of mechanical complexity.

Almost 40 years ago, M.J Lighthill [6] published a study of the superiorhydrodynamic efficiency of aquatic animal propulsion Since that time, therehas been a growing effort to capture the benefits of fish-like modes of propul-sion for use in man-made vehicles It is generally undisputed that the fish-likepropulsive motion is possibly superior in efficiency relative to propellers, yet

it has not been attempted in the design of large scale submersible vehicles

In fact, modern submarine design has focused on reducing the disturbance

of the flow around the hull, whereas fish create large disturbances in the ter This incredible, nonintuitive design demands our attention and makesthe study of fish-like propulsion very interesting and worth studying Wateroccupies 70% of the planet, thus it is clear that in times of constantly acceler-ating human activity and rapidly decreasing energy resources it is needful toimprove the current liquid environment propulsion mechanism, which haveremained fundamentally the same since Archimedes designed his screw inthe 3rd century BC The screw propellers are still used on most of marineand underwater applications such as ships, submarines, underwater robotsetc Although using high amount of engineering skills and human knowl-edge these devices will work sufficiently for most purposes, complex systemsdesigned by nature still outperform them in various aspects

The STARFISH 1 (Small Team of Autonomous Robotic FISH) project [7]was started in 2006 with an aim to develop a platform to test advancedAutonomous Underwater Vehicle (AUV) technology including algorithms forcooperative AUV missions The first major milestone in this project was

achieved in 2008, with the first STARFISH AUV (christened the BlueStar)completing a 4 km long navigation mission in Pandan reservoir and a maidenvoyage in the sea at Selat Pauh The AUV design was refined based on thelessons from the BlueStar AUV, and a second STARFISH AUV was built

in 2009 In early 2010, deployment of both STARFISH AUVs was plannedtogether for a joint mission to locate an underwater target

Although a number of milestones have been achieved in the STARFISHproject, there is much to be done to make AUV teams operate reliably inopen waters The focus of STARFISH 2 [7] was on the ease of operations ofthe STARFISH AUV, safe and reliable autonomous behavior of the AUV, andthe use of the AUVs in small cooperative teams Along with this, we wouldalso like to explore some new technologies that may become important to theAUVs of the future Specifically, the following components to the projectwere proposed: Online system identification; Obstacle avoidance; Vectoredthrust; Bioinspired technologies and Emergent behavior New technologiesthat may be important to AUVs of the future were proposed It includedexploring some bioinspired technology that may increase the efficiency andmaneuverability of future AUVs A significant amount of research into col-laborative AUV teams is also needed to understand how the teams can beused effectively and robustly

Autonomous underwater vehicles (AUVs) have become a main tool forsurveying the sea in scientific, military and commercial applications [2] Themain functions of the AUVs are sensing, control, navigation and commu-nication The main propulsion and trajectory of AUVs are controlled bycontrolling the thrust and speed of the actuators (mostly electric) responsi-ble for the forward motion [1,2,3] The path trajectory is controlled by themain controller in conjunction with the power electronic controlled actuators

The communication to the base station is made through wireless sion The existing AUVs are big in size and non-flexible in nature and henceassociated with maneuverability related problems The straight forward mo-tion is quite good but it needs a lot of area (large turning radius) to turnand also suffers from ’stuck in rocks/sea-weeds’ kind of problem The presentAUVs shape is like a torpedo or submarine as shown in Fig 1.1(a) and hencedoes not serve the stealth purpose in many defence related applications.Modifications on the structure of the AUVs called bio-inspired underwatervehicles (BAUV) have been proposed [7] to overcome the above said problems.The whole structure is divided into three parts: the body, tail peduncle andtail fin The shape is more like a biological fish as shown in Fig 1.1(b) Themotion of this structure replicates fish movements and has better turningand maneuvering capability These next generations of AUVs replicate themovements and work based on fish locomotion The movements of fish-likeAUVs are found to be better than those of conventional AUVs The roboticfish movements are controlled by the fin movement.

transmis-(a) Starfish 2 (b) NUS Robotic FishFigure 1.1: AUV and Bio-inspired AUV

The fin movement is controlled by a single electric motor controlling themotion of a shaft grooved in a particular fashion to replicate the fish motion.Under these conditions a better solution could be that the fins must be con-trolled by several electric actuators instead of mechanical shaft motion If

every segment of the fish is controlled separately then the motion has moredegree of freedom and can sustain high turbulence [7,9] The existing motionscheme of the motors is controlled in a particular fashion such that a fixedsinusoidal motion of the fin movement is mimicked But in practical case thefin movement is governed by many factors such as turbulence, speed of therobotic-fish, obstacle etc and therefore need not follow a fixed sinusoidal pat-tern If the natural fish movement is mimicked then the communication andcoordination among the units are especially crucial The research methodol-ogy and technology of vehicle0s navigation is very crucial to the localizationand the recovery of robotic-fish in open water [2,7,8] It is also expected

to explore the use of sensors that could imitate the sensory organs of thebiological fish that a school of fish use to regulate their movement

So the advanced robotic-fish [7] is expected to behave closely to the ral fish In order to provide a solution for the above said problems, a proposal[7] came through to develop the structure of the AUV with multi-actuatorbased control mechanism through the artificial brain of the fish for motioncontrol The artificial brain of the fish would be implemented using the finitestate machine or neural network structure with decision making capabilities.Sensors would be used on the body of the robotic-fish to detect the move-ments in water and also cameras have to be used to develop the eyes of thefish for distance sensing and obstacle avoidance detection mechanism Thesensors will be coordinated in the desired way by using the artificial brain.The development of such a proposed structure can mimic the fish working

natu-in a better way The natu-increase natu-in the number of electric actuators, sensors,cameras and communication signals increases the complexity of the prob-lem However, with the availability of new generation of power electroniccontrolled actuators together with high-speed and high-computational-power

digital signal processors such complex control algorithms can be implemented

to control the advanced robotic-fish As an alternative to using netic motors as actuators, it is suggested that electro-active polymer materialcan be used as actuators [4] for the same objective As compared to elec-tromagnetic actuators, the electroactive polymer based actuators are simple

electromag-to control, lighter in weight and smaller in size However, they suffer fromrepeatability related problem as well as generating high thrust It is proposedthat further research work needs to be carried out to look at these problemsalso

All kind of processes in the robotic-fish project for example, motion trol, sensing, signal transmission, etc are implemented using hardware elec-tronics circuits in conjunction with a strong software support In this project,digital controllers such as microcontrollers and DSPs have been used Thesecontrollers use electric energy for their functioning Here, the batteries [1,4]act as energy source for the BAUV’ Since batteries have finite energy andtherefore limited life-time, energy harvesting can be considered to supplementthe on-board energy storage device to extend the life-time of the robotic-fish

con-In the oceanic environment, energy is available in the form of ocean currents

- two main types of ocean currents exist: marine currents and tidal currents.Both of these types of currents can act as source of energy to be harvestednot only for main propulsion of the AUV s but also for meeting the energyrequirements of various types of sensors used [1,3,4] The ionic polymers andpiezoelectric materials when excited by an electric source bend in a particulardirection and can be used to be the muscles for the robotic-fish [3,4] On theother hand, such materials when forced to bend or vibrate mechanically theygenerate electric potential and can be used as energy harvesters [4] In thiscase, since as both operations are needed i.e actuation as well as generation,

we are proposing to develop electric muscle as well as energy harvester to tapenergy from the ocean for the proposed robotic-fish The harvested energy isfurther converted to electrical energy and then used to power up the batterieswith an optimal power management system The reliability and performancedegradation are the key issues related to ionic polymers and piezoelectricmaterials and further in depth research needs to be carried out to evaluatetheir suitability for robotic-fish application.

In Starfish 2, a robotic-fish is proposed very near to the realistic fish ing decision making capability, artificial brain like controlling structure, arti-ficial eyes, higher sensing capability with more degree of freedom in motion,optimal trajectory tracking system, robust control mechanism and efficientenergy management system with the possibility of energy harvesting capa-bility In this first-stage of the research work, a scale-down model of therobotic-fish was developed for performance evaluation in the test-tank envi-ronment and also tried out in the swimming-pool environment Depending

hav-on the success of this 1st phase of trial in the sechav-ond-phase a full-scale sion can be developed for the real world environment such as in the reservoirand/or sea Moreover, in this phase of research work, the fish would swimvia a pre-programmed trajectory tracking path rather than through remotecontrol mechanism Subsequently, at a latter stage the option of a remotecontrol operation can also be incorporated

In the past decades, both scientists and engineers have devoted themselves toovercome the drawbacks of the conventional vehicles, and these attempts in-clude multi-screw propellers, rudders, biology-inspired propulsors and so on

Among them, biology-inspired approaches are difficult for practical tions, but they are expected to be comparatively effective and feasible Asmatters of energy economy and greater locomotion performance are desired

applica-in engapplica-ineered systems, imagapplica-inative solutions from nature may serve as theinspiration for new technologies Several physico-mechanical designs in fishevolution have recently inspired robotic devices for propulsion and maneuver-ing purposes in underwater vehicles [1,9,14] It is obvious that the potentialbenefits from biological innovations can be applied to systems operating inwater with a high speed, reduced detection, energy economy, and enhancedmaneuverability Certainly, various fishes may possess different functionsand provide distinct enlightenments Therefore, it is helpful to be conscious

of fishs classification and functions as shown in Fig 1.2 [9] According toWebb [10], aquatic locomotion can be classified, in terms of propulsion, intotwo styles: BCF (body and/or caudal fin) and MPF (median and/or pairedfin) Hereinto, BCF locomotion prevails in high speed and superb acceler-ating ability, while MPF locomotion has a great potential to achieve bettermaneuverability as well as higher efficiency than BCF locomotion

Fish have the ability to turn in less than a body length, and from a ing start, fish can accelerate rapidly using only a few flicks of their tails atlevels of more than 10 g’s Locomotion in fishes is accomplished through asequential system of smaller muscles which contract in a wave along the fish’sbody Once they begin to move, fish utilize their sensory system to detectvortices created by their tails and ”push off” of the vortices which allows them

stand-to be very efficient swimmers This ability stand-to take advantage of sensory back allows them to avoid obstacles, make quick maneuvers, and become asagile as possible in the underwater environment In addition, fishes have de-veloped different shapes and body geometry in order to swim efficiently Two

feed-Figure 1.2: Fish Swimming Modes Classification

of the most common types of fish bodies are carangiform, of which the water largemouth bass is one example, and thunniform, of which the tuna is

fresh-an example These two body types are not extremely different, fresh-and both areefficient swimmers The difference resides mostly in the body taper to thetail fin and in the geometry of the caudal fins On the basis of propulsionbody and/or caudal fin propulsion can be divided into 5 subgroups: anguil-liform, sub-carangiform, carangiform, thunniform and ostraciiform Anguil-liform swimming involves undulatory motions, meaning that the transversalwave is moving through whole body Ostraciiform swimmer generates oscil-latory motions, in which the propulsive structure swivels without exhibiting awave formation Sub-carangiform, carangiform and thunniform motions are

in between undulatory and oscillatory motions sorted by the ratio of thesetwo types There is a great variety of different types of fish propulsion mech-anisms Two most generic categories of these are periodic swimming andtransient swimming Latter is used for rapid starts, escape maneuvers andturns Periodic swimming is used for steady, sustained locomotion The clas-

sification for fish periodic swimming was presented by Breder et al [11] in

1926 and although criticized, it is still in use today According to this sification there are two main families of swimming: body and/or caudal finlocomotion (BCF) and median and/or paired fin locomotion (MPF) Fishesusing BCF locomotion bend their bodies into a backward-moving propulsivewave that extends to caudal fin while fishes using MPF locomotion use theirother fins to propel themselves The manifold contribution of bio-inspired

clas-or bio-mimetic robotics has been both continuously increasing through thelast decade Bioinspiration reflects the features and capabilities of naturalevolution of a system that could be efficiently replicated or mimicked in ahuman engineered system to the design of new technologies and the improve-ment of conventional ones One of the important focused technologies hasbeen the development of autonomous underwater vehicles as a greater part

to the increasing interest in unmanned underwater surveillance and toring Of particular interests are regions of the underwater environmentthose are unexplored and dynamic as well as underwater detection, pollutionsource tracking, underwater archaeology, search and rescue, and so forth

moni-A bio-inspired approach in the design of underwater vehicles i.e inspiredfrom nature has shown credibility for the design of vehicles suitable to bothvehicular morphology and methods of locomotion The study of underwaterevolution of life and its plethora of locomotion modes has long been a subject

of interest to the Biological Community Aligning to the research interest ofthe aforesaid, the Engineering Community has taken up the further tasks

to construct mechanisms that show or replicate the behaviour of swimminglife-forms and their motion Majority of conventional designs of autonomousunderwater vehicles used propellers as their principal mode of propulsion

1.4 Related Work

The famous paradox formulated by Gray studies the propulsion power of thedolphin swimming [12] Gray estimated among other things the power neededfor a dolphin of length 1.82 m to swim at a speed of 10.1 m/s This he did

by calculating the dolphins resistance by means of a drag coefficient based

on a turbulent boundary layer He found that the required power was bly about seven times the estimated muscular power available for propulsion.This yields the paradox which is considered by a large number of investiga-tors The paradox is, however, rather difficult to tackle because of the lack

possi-of a common opinion among investigators on the influence possi-of the swimmingmotion on the resistance of the body Some opinions are that the resistance

of the swimming body can be increased by a factor of three with respect tothe resistance of the body when it glides motionless through the water SirJames M Lighthill Memorial Paper [6] bears only upon part of the manyactivities of Sir James Lighthill, namely upon the mathematical theory ofthe swimming of fish and cetaceans It is well-known that Sir M.J Lighthillconsidered many aspects of fluid mechanics Besides his mathematical ap-proach to fish locomotion Lighthill went, as he says himself with the help ofcolleagues in zoology, deeply into the biological background of the differentphenomena that he investigated in fish swimming which later contributed tothe mathematical foundation of the subject

The RoboTuna project shown in Fig 1.3 was started in 1993 with theobjective to develop a better system of propulsion for the autonomous un-derwater vehicles The tuna was selected as a model for its speed (a bluefin tuna can go up to 74 km/h) and its accelerations It is a question ofunderstanding how a fish can generate enough energy to reach such speeds

This one includes eight vertebrae and a system of cables which is used astendons and muscles The envelope is made up of a fine and flexible layer offoam covered with Lycra to approach the flexibility and smoothness of thetuna skin RoboTuna was suspended by a mast which is fixed at a systemwhich slides along the tank allowing it to rotate and pulled out of the waterfor robot maintenance and storage The mast is also used to pass the cableswhich connect the robot to the controllers Thus, the controllers receive infor-mation from the sensors in entry and return instructions to RoboTuna Themajor structural component of the robot fish is a segmented backbone made

up from eight discrete rigid vertebras which are driven through an elaboratesystem of pulleys and cable tendons by six brushless DC servo motors Thesetendon drives are the mechanical analogy of the biological fish’s muscles

Figure 1.3: Robo-Tuna II built in MIT 1994 with lever, pulley and ball

bearing mechanisms

The NMRI (National Maritime Research Institute) developed many projectsFig 1.4 of robotic fish (series PF and seriesUPF ) with a view to apply, inthe future, the capacities of fish to our boats and submarines The PPF-04 isone small robotic fish of 19 cm and 400 g, remote controlled Its size makes it

possible to test it in a small tank (like a bath-tub) The study carried, interalia, on the relation between the speed and the amplitude of the oscillations

of the caudal fin

Figure 1.4: PPF-04 Uni-link robot fish design by NMRI, Japan

The SPC-03 measures 1.23m in length and is stable, very handy, and iscontrolled remotely by technicians It can work 2 to 3 hours in immersion, atthe maximum speed of 4 km/h This robotic fish is intended for underwaterarchaeological exploration but the two persons in charge for the project, WangTianmiao (BUAA) and Tan Min (CASE) Fig 1.5 considers many otherapplications such as underwater photography, cartography of the underwaterflora and fauna, transport of small object, etc Result of several years ofresearch, the robot was tested in August 2004 on the site of a maroonedwarship The robotic fish explored a surface of more than 4000 sq.m over

6 hours of immersion It took many photographs and transmitted to thesurface

The objective of the ROBEA-Eel project Fig 1.6 was to ”design, studyand produce a robotic eel able to swim in three dimensions” Certain fish as

Figure 1.5: Robotic Fish Chinois SPC-03 developed in BUAA-CASIA

China for underwater exploration

tuna have a mode of locomotion based on oscillations of the body, whereasthe locomotion of anguilliform fish (eel, lamprey ) is based on undulations

of the body Thus, the swimming of eel presents remarkable performances

in term of manoeuvrability It is the high number of internal degrees offreedom of this fish which enables it to thread in the most difficult places ofaccess The prototype of project ROBEA consists of a stacking of platforms

of the kneecap type, imitating the vertebrae of eel LAG, Laboratoire ofautomatic of Grenoble, set up the control systems of the movements of the eel(orientation, speed) as well as stabilization in rolling of the robot Developedwith the BIRG (Biologically Inspired Robotics Group), the BoxyBot projectaimed at the realization of an autonomous robot of various forms and thosewhich uses the fins, like the labriform type and ostraciiform These fisheshave a rigid body and a low speed but a great maneuverability thanks totheir fins In fish of the labriform type, the pectoral fins are used for thepropulsion and the caudal fin is used as rudder BoxyBot is 25 cm long andcan swim up to 0.37 m/s It can plunge, swim ahead, behind, on the side and

carry out gimlets The speed depends on the amplitude and the frequency ofthe oscillations on the fins and also size and rigidity of those.

Figure 1.6: Robotic Eel Angulliform Fish (Robea Project) developed in

CNRS France

A fish has various modes of displacement (speed, turns, accelerations andbraking) and the challenge of the researchers of Essex University was to ob-tain an autonomous robot-fish G8 which can reproduce all these behavioursand not in one or two instances but in a more or less uniform way Theythus indexed the various behavior in a library used by the computer to gen-erate varied and unexpected trajectories of stroke Robotic fish Fig 1.7 (50

cm length) is able to curve its body according to a great angle in a muchreduced time (approx 90/0.20sec) Several models were designed, since G1

in 2003 until G8 and G9 in 2005 The researchers continue to work on theimprovement of the algorithms of training which make it possible for therobot to generate adaptive behaviors in a changing environment and thusremain unpredictable A robot-fish inspired by the carp koi was presented

in March 2006 in Japan It was developed by three companies of whichRyomei Engineering, a subsidiary company of Mitsubishi Heavy Industries,which are already at the origin of the series ”Mitsubishi Animatronics”, was

a key player The robot, which measures 80 cm and weighs 12 kg, was remotecontrolled Its mouth was equipped with sensors being used to control the

oxygen concentration in water, information essential if one wants to supervisethe health of fish In a second step, the researchers want to make their robotautonomous Thanks to its camera, the robot could be sent in recognition toexamine the resources present in the depths It could be also used to inspectthe oil platforms to locate and supervise possible damage Jessiko Fig 1.8

is one of the smallest robotic fish in the world (20cm/100g) Thanks to itscommunication potential and its artificial intelligence, Jessiko can swim in aschool of 10 fish or more, so that they make attractive aquatic and luminouschoreographies At first, it is designed for the events market and aquaticmuseums After, it was announced to mass market as a kit to enliven poolsduring long summer nights

Figure 1.7: Essex G8 Robotic Fish diving mode in water

The ”Robofish” of the University of Washington measures a half meterlong and weighs 3kg It is highly manoeuvrable and can swim backwards

by inverting pectoral fins Since radio signals travel badly in salt water, asystem that allows robots to communicate was studied through this project.During the experiment, Robofish broadcasted their headings to each other,

and used any information received to adjust their own courses According

to Kristi Morgansen, the group remained coordinated despite about half ofall information packets being lost - showing that the system was relativelyrobust With the same technique, it will be possible to explore large areas,track a pollution spill, or to report the location of marine animals

Figure 1.8: Jessiko V4 Robotic Fish developed in France by RobotSwim

Researchers of the School of Mechanical and Aerospace Engineering fromthe Nanyang Technological University, Singapore also studied fish propulsion.Their objective was to design and optimize robotic fish using undulating finmechanisms Thus, for experiments they designed different types of roboticfish like a stingray robot, a knifefish robot, an arowana robot shown Fig 1.9.Engineers at the University of Kitakyushu, Japan have developed one of themost realistic bioinspired robots in the world This red snapper is actually arobotic fish known as Tai-robot-kun Tai-robot-kun weighs 7 kg and mimics

a real fish swimming silently in the water, and can go for as long as anhour with a full battery It has a silicone body covered in realistically hand-painted scales, features a unique propulsion system that allows it to move itstail and drift silently through the water like a real fish Conducting polymer(CP) materials exhibit significant volume change in response to electrical