Design and Control of a Field Deployable Batoid Robot

Audren Cloitre, Vignesh Subramaniam, Nicholas Patrikalakis, and Pablo Valdivia y Alvarado

Abstract— This paper presents our latest results in thedevelopment of biomimetic batoid robots. Our goal is to utilizethese robots for autonomous environmental exploration andmonitoring missions in coastal environments. These new robotswill be part of a larger heterogeneous robotic network alreadybeing developed by our group which combines traditionalrobotic vehicles with biomimetic ones to leverage advantagesof both approaches. The robot described in this paper isdesigned to be fully field deployable and applies importantlessons learned during the development of previous flexibleunderactuated batoid robots. The robot design including itsflexible underactuated continuous body, communications, andcontrol hardware and software approaches are described.Preliminary trajectory control results are also detailed.

I. INTRODUCTION

The first biomimetic underwater robots were introducedabout 15 years ago. Robots like the RoboTuna developedby Triantafyllou et al. [1] at MIT were among the firstmachines able to reproduce the motions of a fish for thedesign of autonomous underwater vehicles (AUVs). Tradi-tional AUVs use propeller based thrust generation to achievepropulsion and maneuverability. However, advantages pro-vided by biomimetic propulsive techniques such as improvedlocomotion performance [1] and maneuverability [2], [3] areundeniable. As a result, the idea to have AUVs that mimicfish propulsive movements arose. Initial studies focused onreproducing the shape and swimming motions of carangiformand thunniform fishes due to their perceived propulsivespeeds. Tail movements were approximated using rigid serialmanipulator assemblies fully actuated by servomotors. Theserobots proved capable of swimming in a controlled fashionand executing basic trajectory control (Yu et al. [4], Dogangilet al. [5], Kato [6], Colgate et al. [7], Morgansen et al. [8]).Valdivia y Alvarado et al. [9], [10] developed an alternativeapproach which exploited the natural dynamics of flexiblebodies to achieve simpler underactuated robots. The resultingvehicles are simpler and more robust than their discretecounterparts. Finally, the reduction in disturbance to the sur-rounding environment from vehicle wakes is also an addedadvantage of using biomimetic motions for locomotion, inparticular for oceanographic studies. Propeller wakes can

The research described in this project was funded in whole or inpart by the Singapore National Research Foundation (NRF) through theSingapore-MIT Alliance for Research and Technology (SMART) Centerfor Environmental Sensing and Modeling (CENSAM).

A. Cloitre and N. Patrikalakis are with the Department of MechanicalEngineering, Massachusetts Institute of Technology, Cambridge, MA 02139,USA cloitre@mit.edu, nmp@mit.edu

V. Subramaniam and P. Valdivia y Alvarado are with the Cen-ter for Environmental Modeling and Sensing, Singapore-MIT Al-liance for Research and Technology, Singapore 117543, Singaporevignesh@smart.mit.edu, pablov@smart.mit.edu

easily disturb fragile ecosystems during monitoring oper-ations while certain biomimetic propulsive wakes do notinterfere negatively with the surroundings.

A. Batoid Robots

In recent years fishes from the batoid family (rays, skates,etc.) have attracted the interest of scientists ([11], [12],[13], [14], [15]). The need for flexibility along the entirebody presented a challenge for biomimetic AUVs based oncarangiform and thunniform swimmers. Batoids on the otherhand, have bodies with rigid centers as their motions areproduced by their pectoral fins. Their rigid body centersfacilitate embedding mechanical components, sensors, andcontrol and navigation electronics. Furthermore, studies onbatoids [16], [17] have highlighted their superior maneuver-ability and performance features. Parson et al. [18] comparedthe performance between undulatory batoids (stingrays) andoscillatory batoids (manta rays) and concluded that oscil-latory batoids were capable of smaller turning radii andfaster angular velocities during banked turns engaged aftera phase of acceleration. The robot presented in this study isthe latest iteration on the family of underactuated compliantbatoids developed by Valdivia y Alvarado et al. [19], [20]. Underactuated compliant batoid robots follow the sameprinciple of exploiting the natural dynamics of flexible bodiesto achieve simpler underactuated robots [10]. In this case, asoft body can be made to replicate the motions of a batoidfish and thus create enough thrust to swim and maneuverunder water.

B. Swimming Control

Work on swimming control of biomimetic AUVs hasalso garnered attention as a natural progression of the workon biomimetic vehicle design. Swimming in a controlledfashion, and point to point trajectory following have beenaddressed both theoretically and experimentally (Yu et al. [4],Dogangil et al. [5], Kato [6], Colgate et al. [7], Morgansenet al. [8]). In this study, a prototype was designed to carryall its critical components on board to enable full autonomyin harsh marine environments. Because of its scale, the robotpresented can carry a power supply (rechargeable batteries),control electronics, and several sensors. Preliminary exper-iments however were conducted with a tether to avoid thehassle of recharging batteries during testing and to facilitatesoftware debugging. Dead weights with the same dimensionsas the batteries were used to keep the balance of the robot.To date, little work exists on the development of fieldablebiomimetic vehicles (Listak et al. [21] developed a robotintended to be fielded in a shallow water environments).

The Fourth IEEE RAS/EMBS International Conferenceon Biomedical Robotics and BiomechatronicsRoma, Italy. June 24-27, 2012

978-1-4577-1198-5/12/$26.00 ©2012 IEEE 707

1 – Silicone outer body

2 – First part of the inner shell

3 – Lock for the dead weights

4 – Dead weights (4 of them, each weighs 250g)

5 – Second part of the inner shell

6 – Third part of the inner shell

7 – Waterproof connector

8 – Nose

9 – Motor EX-106+

10 – Support for the insert #12

11 – Frame to couple the insert with the motor

12 – Flapping insert

13 – Pressure sensor

14 – Mount for the pressure sensor

15 – GPS unit

16 – Mount for the GPS unit

17 – Inertial Measurement Unit (IMU)

18 – Buoyancy tank assembly

19 – Cover of the shell

20 – Cover of the connector box

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Fig. 1. Robot body design: Isometric exploded view (top), isometric view (bottom left), front view (bottom right). All views show the robot upside downto facilitate part visualization.

Our goal is to contribute in this area by presenting a novelalternative for the design and control of biomimetic vehiclesthat can be deployed in a harsh environment.

The structure of the paper is the following: section II cov-ers the robot design, section III explains the control algorithmand details our experimental results, the preliminary resultsare discussed in section IV, and conclusions and future worksare summarized in section V.

II. DESIGN

The design of this robot is based on a soft polymer bodyand mimics the morphology and kinematics of rajiform orundulatory batoids (i.e. stingrays). A rigid shell embedded

inside the body is used to house all the components the robotneeds for locomotion and autonomy. The components includeactuators, batteries, a buoyancy tank, and the control andcommunication electronics. Fig. 1 shows different views ofthe robot design and all its components. The robot featuresare explained in the following subsections.

A. The body

The main feature of this robot is that it is a soft robot(Fig. 2) as opposed to a traditional robot composed of anassembly of rigid mechanisms. This choice is motivatedby the undulatory motion of a real stingrays. Instead ofactuating the pectoral fin with a set of motors to recreate

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Fig. 2. Robot body assembly: bottom view of internal mechanism (left),internal mechanism embedded inside flexible body (right).

the propagating wave in the fin; the idea is to choose asoft material whose response to a sinusoidal input wouldbe the propagating wave of a real stingray. This approachreduces the complexity of the actuation. It also requires lessenergy and is less susceptible to a mechanical failure [19],[20]. Silicone presents appropriate material characteristics interms of modulus of elasticity and viscosity. Since thoseare the key factors that parameterize the response of thematerial to an excitation, this material was chosen to buildthe body of the robot. However, the material properties ofsilicone should vary along the geometry of the body in orderto exactly recreate the motion of a real stingray [19]. Asmanufacturing such a robot is a challenge and since thisrobot is a prototype, the body was built using only onegrade of silicone. Nevertheless, the motion is approximatedsufficiently well to have the robot swim underwater.

1) The shell: Just like a real stingray, the center part of therobot’s body is rigid. This feature enables embedding com-ponents inside the robot without modifying its kinematics. Inorder to maximize the space inside the shell, it was designedto reproduce the shape of the outer surface of the body (Fig.2). For convenience, the shell was composed of several parts(three in total) (parts 2,5 and 6 in Fig. 1) manufacturedusing a 3D-printer. This process is fast, enables us to createcomplex shapes without difficulties, and it is repeatable. Theshell was coated with epoxy to strengthen its structure andseal any gaps between the parts. A flat carbon-fiber covercloses the shell. This cover is made in two parts (parts 19and 20 in Fig. 1). The smaller part gives access to a boxinside the shell that contains the connectors for the batteriesand the controllers. That way, only a small portion of thebody needs to be cut open to access the inner components.The induced hole can be refilled easily by adding silicone atthis location.

2) Actuation: Only three actuators are needed to controlthe robot. The servomotors used are controlled through serialcommunications and they can provide position feedback.They also have temperature and load sensors which candetect an abnormal use of the motors. Two Robotis EX-106were chosen to actuate the two pectoral fins and one RobotisRX-28 actuates the buoyancy tank. An exploded view of theactuation of the fin can be seen on Fig. 1 (parts 9 to 12), aswell as its implementation on the shell.

1 – Motor RX-28

2 – Oldham coupling

3 – Oldham disc

4 – Half Oldham coupling

5 – 30 mL syringe

6 – 60 mL syringe

7 – Plunger for 30 mL syringe

8 – Plunger for 60 mL syringe

9 – Plunger pusher

10 – Lead screw

11 – Nut for lead screw

12 – Slide rod

13 – Bush

14 – Bearing

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Fig. 3. Buoyancy tank: exploded view of assembly (top), bottom view ofprototype (bottom).

3) Buoyancy tank: A buoyancy tank allows depth changecontrol and can be used to complement swimming motions.The tank is composed of four syringes; for a total volumeof 0.18 liters. As it represents only 3% of the total volumeof the robot, the mass of the robot needs to be carefullydesigned. The syringe plungers are attached to a nut on alead-screw system. The lead-screw is coupled to the RX-28servomotor. Two kill switches prevent the nut from goingover the track length. Fig. 3 shows an exploded view of thebuoyancy tank mechanism and the assembly inside the robotshell.

4) Batteries: Batteries were chosen to provide enoughenergy to the robot for about one hour of autonomy. SinceLi-Po batteries offer the best power density on the marketthey were chosen for the prototype. The prototype testedwith a tethered external power uses dead weights of thesame dimensions and density to compensate for the lack ofbatteries during preliminary tests.

5) Electronics: The major components are the micro-controllers and sensors. Two micro-controllers are used, anMBED collects data from the sensors, decides the behaviorof the robot and communicates with the operator, a CM700controls the servos with respect to the orders received by theMBED. Thanks to this architecture, the robot can multitaskeasily, pursuing a motion while preparing the next one. The

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TABLE IHARDWARE DETAILS

Diameter (L) 0.61 [m]Weight 6.1 [kg]Volume 0.00615 [m3]GPS D2523T by Adh-TechIMU CHR-6DM by ChroboticsActuators Robotis EX-106 and RX-28Batteries Voltron LiPo 4S 55C 3[Ah]Number of Parts 59Communications Xbee Pro 868Processors Mbed by Mbed.org and CM700 by Robotis

orientation of the robot is given by an IMU with an integratedextended Kalman filter. A GPS unit gives the position of therobot. With those two pieces of information, the robot canperform a waypoint following trajectory. Finally, a pressuresensor gives feedback on the robot depth. Details of the robothardware are listed in Table I.

III. CONTROLS

A. Approach

A model-based control is very complicated to implementfor this type of robot. The underlying locomotion dynamicsinvolve high-order partial differential equations a micro-controller cannot solve. To avoid solving for the dynamics,an intuitive controller has been developed. Preliminary ex-periments have shown the robot to be able to realize full turnswhen one of its fin is shut down and the other is operatedat frequencies between 1 and 2.5 [Hz]. Maintaining the twofins flapping at the same frequency will result in forwardmotion. Since the only two motions necessary to achievea waypoint following trajectory are forward swimming andturning by a determined angle, we can build a simple singleinput single output (SISO) controller to set a frequencydifference between the two insert sinusoidal motions and usethe measured robot yaw for feedback. This first low-levelcontroller would be able to maintain the robot’s heading.

B. Experiments

1) Setup: Experiments were conducted in an open airswimming pool (Fig. 4). The buoyancy tank was set to keepthe robot at the surface of the water so that pitch and rollwere kept at a zero angle at all times. Also, a bias was addedin the sinusoidal motion in order to keep the fins below thewater. The cable used to tether the robot was 10 [m] longand allowed the robot to run in a straight line for about 15[m]. The computer and power supply were kept at the side ofthe pool during the entire operation. A camera was placed ata high spot to record the motion of the robot. However, wecould not find a spot high enough to film vertically the fullrun of the robot. Thus, external video could not be used forposition monitoring. Data was logged in a text file directly onthe flash drive of the MBED micro-controller. It incorporatedthe measured yaw of the robot at each sample time as wellas the values of the two frequencies at that moment in time.

Fig. 4. Prototypes were tested in an open air swimming pool.

TABLE IICONTROLLER PARAMETERS

Difference of frequency δ fFrequency of the left fin fle f tFrequency of the right fin frightYaw reference ψre fMeasured yaw ψmeasuredProportional gain Kp (0.05 [Hz/deg])Nominal frequency fnominal (1.4 [Hz])

2) Heading control: The controller was coded on theMBED. At every sample time, the updated frequencies weretransmitted to the CM700 which takes care of the motionplanning of the motors. A constraint was added to keepthe control loop SISO. As the output of the controller is adifference of frequency between the two motions of the fins,a nominal frequency has to be set and used as reference forthose two frequencies. This reference is arbitrary and waschosen after a qualitative observation of the behavior of therobot run in open-loop. In order to prevent an overload onthe actuators, saturation limits were also implemented. Wechose to keep the lower saturation at 0 [Hz] and to set theupper one at 2 [Hz]. Just like for the nominal frequency,the upper value was chosen based on experience gainedduring open-loop trials. For our first controller we decidedto implement a proportional controller as this controller typewas the simplest to implement. It was able to give us anidea of the preliminary performance we should expect fromthe robot and its ability to keep a given reference yaw. Thecontroller parameters are defined by the following relations:

δ f = Kp ∗ (ψre f −ψmeasured)

fle f t = fnominal−δ f

fright = fnominal +δ f

where the variables used are defined in Table II.Preliminary experimental results are shown in Fig. 5. The

plots show the error in yaw e and the change in frequencyfor each actuator, FL and FR versus time for two test runs.

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Fig. 5. Experimental results. Yaw error e in degrees, and change in frequency of each actuator FL and FR in 10∗[Hz] versus time t in seconds.

The change in frequency is scaled by a factor of 10 in orderto visualize them along with the error in yaw.

IV. DISCUSSION

The results so far proved the robot is capable of maintain-ing a given heading for about one minute using a very simplecontroller. We could not operate the robot for a longer timeas the length of our cable was limited. The first observationsmade from these results include the beating in the yaw error eas well as the slow pace at which the difference in frequencyis updated. Consider the results obtained for t ∈ [26;33]seconds on the bottom graph of Fig. 5. The error in yawkeeps on increasing despite an increase in the differenceof frequency, δ f . Here, the proportional controller is notefficient enough. The controller should also have a derivativeterm that would react to such an increase in the error overtime. Moreover, at t ∈ [9;21] seconds in the top graph and att ∈ [40;50] seconds in the bottom graph the error in yaw staysconstant for an extended period of time. It is indeed possiblefor the robot to keep a given heading even though it flapsits fins at different frequencies. This situation occurs when across flow hits the robot such that the hydrodynamics of eachfin are no longer symmetrical. In such a case, a balance canbe found between the dissymmetry in the hydrodynamicsof the fins and the dissymmetry in the input frequency ofthose fins. An integral term in the controller could addresssuch a behavior and increase δ f even if e remains constant.However, even if a perfect controller were to be designed(one that would keep the error in heading null at all times)it will not guaranty the robot will go in a straight line.As the robot swims in fluids that are also in motion, therobot can drift from its route. Another control loop shouldbe implemented to detect this drift and a controller should

Fig. 6. Diagram of control architecture

update the reference in yaw so that the robot can correctits trajectory and reach any given waypoint. See Fig. 6 tovisualize the architecture of this controller. Fig. 7 presentsthe configuration at which the robot will find itself after adrift and the parameters the controller will need to computethe correcting angle, ψdri f t .

V. CONCLUSIONS AND FUTURE WORKS

A. Conclusions

This study presents the design for a prototype of a fielddeployable biomimetic stingray. The robot uses a soft bodyunderactuated approach and all mechanical and electroniccomponents needed for autonomy are embedded inside thebody. The design proved capable of successfully achievingseveral runs outside of a controlled laboratory environmentand it showed encouraging results for trajectory control.The robot scale will be able to accommodate oceanographicsensors useful in environmental surveys and other monitoringactivities in coastal environments. A simple classical SISO

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Fig. 7. GPS orientation

controller was used to test trajectory control and start explor-ing the challenges of controlling the complex hydrodynamicsneeded for batoid locomotion.

B. Future Works

Planned next steps include improving the control approachand upgrading parts of the hardware design. The headingcontroller can have better performance with the changesdiscussed earlier and a GPS based position monitoring con-troller would allow a waypoint trajectory following. InertialNavigation is also considered in order to keep track of therobot’s position even when a GPS signal is not available.Longer tests will be carried out to determine new controllerperformance and turning experiments will be carried out totest maneuverability. A model-based controller will also bedeveloped where the relationship between fin actuation andresulting propulsive forces will be determined empirically.

VI. ACKNOWLEDGMENTS

The authors gratefully acknowledge G. Weymouth for hishelp during field experiments.

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