technical design report of matsya 6, autonomous underwater … · 2020. 8. 10. · tejas bhalla,...

AUV-IITB, INDIAN INSTITUTE OF TECHNOLOGY BOMBAY 1

Technical Design Report of Matsya 6,Autonomous Underwater Vehicle

Aditya Biniwale, Sudarsanan Rajasekaran, Ninad Kale, Anant Taraniya, Akshat Raj Lad, Mohan Abhyas,Sanjoli Narang, Vyankatesh Sawalapurkar, Sudhanshu Nimbalkar, Parth Patil, Piyush Tibarewal, Nayan

Barhate, Aditya Harakare, Anuj Agrawal, Shaunak Natarajan, Shubham Tiwari, Nandagopal Vidhu,Nakul Randad, Advait Padaval, Balla Sarat Chandra, Rishabh Singh Dodeja, Andrews Varghese, ApurvaKulkarni, Ruchir Chheda, Vatsal Srivastava, Chaitanya Tate, Aditya Gupta, Anshuman Rathore, ShibaniDhar, Kruthagnya Siri Myana, Aayush Shrivastava, Ayushi Gupta, Parvik Dave, Shiv Modi, Akshat Zalte,Nirmal Shah, Pranjal Jain, Sudarshan Gupta, Vikram Atreyapurapu, Devansh Jain, Sidharth Mundhra,

Tejas Bhalla, Vignesh Anand, Anagha Savit, Akash Fokane, Ramyasri Palti, Sabhya Sanchi, VinayakSaxena, Mayur Sanap, Gaurav Kohad, Dileep Mukera, Sachin Bhuibar

Faculty Advisors: Prof. Leena Vachhani and Prof. Hemendra Arya

Abstract—Matsya, is a series ofAutonomous Underwater Vehicles (AUVs)being developed at the Indian Institute ofTechnology (IIT) Bombay with the aimof delivering a research platform in thefield of underwater robotics and promotingautonomous systems. Major architecturalchanges have been made to the subsystemsby designing them from the perspective tohandle tasks in real time. Some of the keyfeatures include improved heat dissipation,debug board, competition friendly missionplanner.

Fig. 1: Matsya 6

I. Competition StrategyThe objectives and challenges at RoboSub

2020 consists of challenging environmentmanipulation. The team approachedthe competition with a major focus onerror-minimized reproducibility of the newvehicle design and increased reliability ofMatsya’s performance in tasks at RoboSub.A critical analysis was done to address theheating issue in the main hull which ledto multiple electrical failures. The problemwas addressed by developing a properheat dissipation mechanism for the two

main sources: Base plate modification forGPU & New ESC hull for the ESCs. Thevehicle design also saw significant changes inpositioning of components as compared toits predecessor leading to a smaller vehiclewith better control.

This year, we set our target as the G-manand its related tasks, due to the verywell-characterized images associated withthem. In order to maximize our score, wewould attempt all bonus tasks: starting ata random position, performing style movesas we pass through the gate, opting for therandom pinger, shooting through both theellipse and trapezium of the torpedo task,dropping markers in the closed section of thebin, and surfacing-up through the octagonwith a bottle.

In order to achieve the above withmaximum confidence, we have madesome major improvements in the softwaresub-system. We have greatly improvedour controller tuning for accurate setpointachievement. This is vital in the Torpedotask and in picking up bottles, as themaximum permissible error margins hereare small. We have fixed the issue of thecameras getting disconnected mid-run byimplementing our very own custom cameradrivers. Also, last year’s mission plannerwas feature rich but very complex, makingit less reliable as we had to provide it with amultitude of parameters just minutes beforea run, making the process error-prone. Hencewe have greatly simplified the planner thisyear.


II. Vehicle Design

Mechanical Sub-system

Core philosophy behind design of Matsya 6- Compactness, Modularity, Reliability. Themechanical design can be bifurcated intoHulls and Frame (Structure and ComponentPositioning). A total of 8 thrusters havebeen used to provide all 6 DoFs tothe vehicle. The vehicle is also equippedwith various manipulation systems (Arm,Gripper, Torpedo Shooter, Marker Dropper).

Hulls: Main Hull: The vehicle has a mainhull which houses all major electronics. Thenew main hull design includes features likelayered and backplane electrical stacking,and a redesigned base-plate to ensure properheat dissipation (direct GPU mounting onthe baseplate to improve heat transfer).

ESC Hull: A new hull was designedhousing all the ESCs (Electronic SpeedController) and elec circuitry in order toreduce the volume occupied by the ESCsand majorly to improve the heat dissipationdue to the 8 ESCs, which caused multipleelectrical failures in the past iteration ofthe vehicle. Interdisciplinary discussions andmultiple design sketches led to a rectangularshaped hull having grooves in the wallsand the base plate for steady contact ofESCs with the hull surface for continuouscooling from the surrounding water. ThePWM signal wires were brought in through aseparate penetrator in order to minimize theinterference and attenuation. This resultedin a reduction of 60 % volume occupied byESC and elec circuitry as compared to thelast iteration and this space in the main hullwas used to accommodate the newly madeboards by the electrical division.

Fig. 2: New ESC Hull

Battery Hulls: Batteries are stored incylindrical battery hulls. Team’s experiencewith cylindrical hulls (Matsya 4) simplifiedthe designing and analysis process. Thisdesign helps in reducing disassembly timeconsiderably, increasing the ease and speedof taking the batteries out (for rechargepurpose). It also increases modularity whichcan in turn help in Cg-Cb balance. A domestructure is added on the front-facing planeof the hull to reduce drag.

Camera Hulls: Matsya-6 has two cameraseach enclosed in a cylindrical camera hullmounted on the front and bottom of thevehicle to cover maximum field of view

Frame: A skeleton type frame hasbeen designed to reduce weight withoutcompromising on strength. It also hashandles to transport the vehicle by hand,and additional handles at the rear end forthe diver. The parts of the frame on whichheavy parts are mounted are designed suchthat it has a high load bearing capacity inthe vertical direction. The parts on whichthrusters are mounted is designed based onthe loading the thruster would be exertingon it.

Manipulators: To perform all possibletasks in the competition Matsya-6 isequipped with various manipulation systemsnamely:

Arm & Gripper: A 1-DoF arm withhumerus and ulna connected by re-voluteelbow joint with a split-finger gripperactuated pneumatic air cylinder.

Torpedo Shooter & Marker Dropper:High-pressure pneumatic actuators are usedfor shooting torpedoes, and marker droppermechanism with reloading capacity.

Fig. 3: Arm & Gripper Assembly


Software Sub-SystemCamera Drivers: We have made theswitch from a third party (AVT Vimba)driver to a brand-new, custom, in-houseimplementation. This has led to a 270%increase in maximum achievable frame rate(52Hz now vs 14Hz earlier). While theearlier driver could not handle a shutdownof the cameras (which was caused byeither power failure/USB connection issues),the new one seamlessly reconnects to thecameras and restarts publishing the videofeed on the corresponding ROS topic.Our implementation also allows us to setvarious parameters like Absolute FrameRate, Exposure and Gain.

Mission Planner: Our previousimplementation, the most powerful wehave ever made, needed multiple parametersto be tuned just before a run. This madeparameter tuning prone to human error,especially in the high-stress RoboSubcompetition. Hence, we have simplified thatplanner and the decision making process isalmost linear. Minimal parameters need tobe tuned just before deployment, makingit very competition friendly. It inheritstask-grouping from the previous design.We have also implemented a pretty printerfor improved clarity in the outputs of theplanner.

Fig. 4: Map GUI tool

Auto Tuner for Controller: Toauto-tune the controller parameters, wehave implemented an algorithm thatstudies Matsya’s motion and uses a binarysearch inspired algorithm to tune thrustercorrection values. These values take into

consideration the offset caused by the centerof mass of Matsya not being in line withthe centre of application of torque. We havealso automated our PID tuning process,achieved by using heuristic methods toderive a model followed by an evolutionaryalgorithm that identifies optimal PID gains.

GUI Tool for Map: As there are oftenhuman errors when entering coordinatesof tasks for the map before the runs atRoboSub, we have created a GUI tool thatallows the user to add tasks, dynamicallyvisualise them in 2D and 3D, and then savethe map as a YAML file when satisfied.

Path Planner and Path Follower: Inthe navigator package, a novel path planningalgorithm has been implemented which plansthe path of Matsya across the map fromstart to end, taking into consideration thelocation of obstacles in the map. It usesbreadth first search paired with some simpleconstraints and heuristic functions. Thispath is then passed to the new and improvedPath Follower which allows the vehicleto move along the specified trajectory,adhering to the given velocity constraints. Ithelps Matsya navigate trajectories smoothly,without taking any sharp turns.

Electrical Sub-system

ESC Hull : Continuing from theMechanical Section of the ESC Hull,many new features were added to thesystem when ESCs were separated from themain hull. This includes a custom madepower distribution box for eliminating wireclutter in the hull, a Mechanical LatchRelay to implement hard Kill by directlydisconnecting the battery in case of failuresand real-time current and PWM monitoringfor each ESC, so that any malfunction ofthe thrusters is known to the system andthe operator for better debugging.

Wiring : Also, this time, wire routingand management was taken with utmost careso that the wiring remains comprehensibleafter the vehicle is assembled. This includedtaking an account of all the wires and theirbending radius, heating properties and otherparameters in the vehicle design itself, so


that debugging and assembly of both MainHull and ESC Hull are super smooth.

Electrical Board Stack : We alsoequipped the main elec-stack of MATSYA 6with a lot of new features offering controlledredundancy and debug capabilities tomitigate in-run failures.

1. A new Debug board is designed thatcaptures data from all the sensors on-boardincluding the electrical stack itself, PWMchannels, thruster current values (from ESCHull) and the motherboard. The data islogged on an SD card for analysis later on.And it’s also sent to the motherboard forany real-time decision to be made on anevent and at the same time displaying thestatus on an LCD screen for easier debuggingin the development phase. We also addedStatus LEDs to get visual feedback aboutthe vehicle state (scanning, or transition orexecution) during the autonomous run.

2. The GPIO board is equipped withtwo different micro-controllers eachcapable of controlling the entire vehicleindependently ensuring dual redundancyand user-selected complexity. The DebugBoard along with the GPIO facilitate amutual feedback and restore system in caseany one micro-controller fails.

3. The power board generates and suppliesall the different voltage levels requiredfor all the sensors, other boards and themotherboard. This year the number ofmutually exclusive toggle lines was increasedfrom four to eight for better control of thepower across the vehicle, implementing otherfeatures like reverse battery and over-voltageprotection as well. The Backplane providesone-point interfacing of the electrical stackwith the sensors and the motherboard.

4. The Backplane Board was redesigned tohouse the Debug Board and all its necessaryfeatures. It now houses the Power, GPIO andDebug board and ensures easy connectionsand routings to all the other peripherals andsensors.

III. Experimental resultsSimulation-based testing is the need

of the hour during this pandemic. Wehave expanded our simulation package’s

Fig. 5: Elec stack of Matsya 6

capabilities by incorporating the UUVsimulator. It allows for more accuratesimulations with its variety of pluginsthat model underwater hydrostatic andhydrodynamic effects, thrusters and sensors,hence allowing us to compensate for the lackof in-pool testing.

Simulation ResultsModels of this year’s tasks were made

using Gazebo’s model editor. OpenCV-baseddetection has been used as our lab’sresources are not accessible due to theCOVID-19 pandemic and we can hence notrun our default YOLO network. OpenCVsuffices here because of the ideal conditionsin the simulator. However, in real lifetesting, it would not suffice and would beentirely replaced by ML-based detection andclassification.

Fig. 6: Gazebo simulation of Torpedo task

1) Gate Task: The gate task this yearhas been made much easier with theinclusion of images at the gate, as wecan now detect the larger images ratherthan the thin pipes making the gate.


Estimated probability of successfullycompleting the gate task: 100%

2) Buoys task: The current buoy isplanar as compared to last year’s,more difficult, prismatic buoy. As wesuccessfully completed last year’s buoy,we are 100% confident of completingthis year’s version.

3) Bin Task: As there are now more visualfeatures to work with (images on thebins have highly characteristic colors),a large improvement is expected in theperformance on the vision side. Theprobability of success for the open bintask is around 90%, while it is estimatedto be 70% for the closed bin task.

4) Torpedo Task: The accuracy ofdetection from the vision side is againexpected to greatly improve becauseof the starkly different shapes and redborders. Our main source of error isin centering the torpedo barrel on thetask, as our error in positioning has tobe lesser than 5cm. Our simulationsshow that shooting through the ellipsehas a 80% chance of being successful,and shooting through the trapezium, a70% chance.

5) Pinger Task: The vehicle has a very highaccuracy of pinger detection and caneasily reach within 60cm of the pinger.The success rate is about 90%.

6) Octagon Task: Increased gripping areaof the arm has increased the chances ofpicking up a bottle. Hence we estimatethe chance of picking up a bottle tobe around 50%. As the tables arewell-characterised, once the bottle hasbeen grasped, placing it on the table orrising up through the octagon with ithave more than a 90% chance of success.

The Mechanical Division performedextensive simulations and experiments tojustify the design changes that were made.

Thermal Analysis of the Main Hull1) Analysed the heating issue of the Main

Hull by performing CFD simulations onANSYS Fluent

2) Conducted proof-of-concept experimenton the temperature dependence of the

heat source on flow rate3) Redesigned the baseplate to mount the

GPU directly onto it, ensuring peaktemperatures below the safety limit of95◦C

Fig. 7: Temperature Distribution of the Base-plate

Pressure Analysis of HullsWe have ensured the strength of the

pressure hulls by running simulations onANSYS Static Structural. Thus, finiteelement analysis is used to check thesafety factor and deformation in hulls whenpressure equivalent to that exerted by waterat target depth is applied.

Fig. 8: Safety factor of DVL Hull at 20m depth

IV. AcknowledgementsWe would like to thank the Industrial

Research and Consultancy Centre of IITBombay for administrative and monetarysupport during the project and for helpingus participate in RoboSub 2020. The supportof the Dean R&D’s office was crucial in thesuccessful execution of the project. We wouldalso like to thank Prof. PSV Nataraj fromSysCon, IITB, for issuing us a GPU on whichwe could train our Machine Learning Models.

We sincerely appreciate the generoussupport from our sponsors. Special thanksto our vendors Blue Robotics and TeledyneRDI for their support in case of technicalproblems.


References[1] Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi, You Only Look Once: Unified, Real-Time Object

Detection 2015.[2] M. M. M. Manhaes and S. A. Scherer and M. Voss and L. R. Douat and T. Rauschenbach, UUV Simulator: A

Gazebo-based package for underwater intervention and multi-robot simulation 2016.[3] Welch, Greg and Bishop, Gary, An Introduction to the Kalman Filter. 1995.[4] Ashok Kumar Tellakula, Acoustic Source Localization Using Time Delay Estimation. 2007.

Appendix A: Component Specifications

Component Vendor Model/Type Specs Cost(if new)BouyancyControl

DesignedIn-House

Dead Weights& Foam - -

Frame DesignedIn-House

Aluminium &Delrin 4 kg 800 USD

WaterproofHousing

DesignedIn-House

AluminiumHulls w/AcrylicEndcap

8 Hulls weighing 22 kgDepth Rating : 70 ft 2100 USD

WaterproofConnectors

DesignedIn-House Aluminium 24 connectors weighing

1.5 kg in total 150 USD

Thruster Blue Robotics T200 11 and 9.5 kgf forwardand backwards 1600 USD

MotorControl Blue Robotics Basic R3

Version30A PWM controlledbrushless motor speedcontroller

200 USD

High LevelControl

MicrochipTechnology

Atmega 328Pand 32M

Low Power CMOS 8-bitRISC Microcontrollers 15 USD

Actuators Janatics A51012025O Stroke Length: 25mm 30 USDBattery Tattu LiPo Battery 4 Cell and 16000mAh x 2 400 USD

Converter TexasInstruments PTN 78060

6A wide input outputAdjustable switchingregulator

50 USD

Regulator Mini-Box M4ATXHigh efficiency 250Woutput, < 1.25mAstandby current

80 USD

CPU Intel Intel i7 i7 8700, 8GB RAM -

GPU Nvidia GeForceGTX 1660ti GDDR5, 6GB, 120W 300 USD

InternalCommNetwork

MicrochipTechnology,CAN USB

MCP 2515,MCP 2551,CAN USB

1 MB’s operation limit 150 USD

ExternalCommInterface

- Ethernet 10-100 Mb/s -

ProgrammingLanguages C++, Python - - -

Compass - - - -InertialMeasurementUnit (IMU)

Microstrain GX5 - -


DopplerVelocity Log(DVL)

Teledyne ExplorerDVL - -

Camera(s) Allied Vision MakoG-243 - -

Hydrophones TeledyneRESONUnderwaterTC 4013

- -

Manipulator DesignedIn-House -

1 DOF servo-operatedarm, pneumatic drivenend-effector

300-350 USD

Algorithms:Vision YOLO v3 - Parallel and Sequential

processing, lens formula -

Algorithms:Acoustics FFTW

Timedifferenceof arrival

Filtering in frequency &time domain -

Algorithms:Localizationand Mapping

Orocos BFLExtendedKalmanFilter

EKF applied on positionfound by integration ofDVL velocity

-

Algorithms:Autonomy -

StateMachine& MissionPlanner

Probabilistic (or Finite)state machine for missionplanner, designedin-house

-

Team size 45 - - -HW/SWexpertiseratio

2:1 - - -

Testing time:simulation 200 hrs - - -

Testing time:in-water 40 hrs - - -


Appendix B: Outreach Activities

The AUV-IITB Team, each year attends many workshops and/or exhibitions to reach thecommunity. It is through these exhibits the team encourages young school as well as highschool students to take up robotics. The team demonstrates working of the AUV followedby a detailed seminar and a questionnaire session to motivate students and increase theirknowledge about AUVs and robotics in general.

Prime Minister of India, Shri. Narendra Modi with Matsya 4 at IITB

We also participated in MTS TECHSYM-2020’s Students’ Technical Symposium OnAdvances In Engineering And Technology, held at IIT Madras, where we interacted withprofessors and students from all across the country who are working on various maritimetechnologies. We presented a poster highlighting the various advances made in Matsya,with the hope of encouraging other AUV teams along their journey. We received a specialmention for the same.

Presenting our poster at MTS TECHSYM, IIT Madras

The team assisted in conducting a week long workshop for the student technicalteam from the Bannari Amman Institute of Technology, Tamil Nadu in the design andmanufacture of AUVs.

Apart from this, the joy it brings to others, especially young enthusiastic school students(for example students of Witty International School shown in photo) is a rewardingexperience and motivates the team further to work harder and continue to make moredevelopments.


School children at our lab

The research that was done by the team also helped several students in theirMasters/BTech projects on topics like Control of Overactuated Nonlinear Systems,Navigation of Unmanned Vehicles, Design of a 2-Link gripping mechanism, and Sunlightflicker removal. This further fuels the team to work harder and deliver results.

The team also mentors quite a few other teams from India, who are keen on makingAUVs, like IEM Kolkata, KJ Somaiya College of Engineering, Mumbai, Sahyadri College,NIT Rourkela, IIT Kanpur and VIT Pune. The team guides them through the overallprocedure of making an AUV, the importance of communication and documentation andthe process of acquiring funds for making AUVs in their respective colleges.

technical design report of matsya 6, autonomous underwater … · 2020. 8. 10. · tejas bhalla,...

Documents