Modeling and Development of an Autonomous Underwater Vehicle ARYA for Object Recognition
Aditya Natu1, Anuj Badhwar2, Vipul Garg3, Upasana Biswas4, Deepanshu Bansal5, Aakash Kumar6
1Aditya Natu, Department of Mechanical Engineering, Delhi Technological University, Delhi, India.
2Anuj Badhwar, Department of Applied Mathematics, Delhi Technological University, Delhi, India.
3Vipul Garg, Department of Mechanical Engineering, Delhi Technological University, Delhi, India.
4Upasana Biswas, Department of Electrical Engineering, Delhi Technological University, Delhi, India.
5Deepanshu Bansal, Department of Electrical Engineering, Delhi Technological University, Delhi, India.
6Aakash Kumar, Department of Mechanical Engineering, Delhi Technological University, Delhi, India.
Manuscript received on 21 March 2019 | Revised Manuscript received on 26 March 2019 | Manuscript published on 30 July 2019 | PP: 5505-5510 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2843078219/19©BEIESP | DOI: 10.35940/ijrte.B2843.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Arya is an autonomous underwater vehicle (AUV) modeled and developed by team DTU-AUV comprising of undergraduate students from multidisciplinary backgrounds of Delhi Technological University (DTU), India, to participate in an IEEE backed Singapore AUV Challenge (SAUVC). This paper entails the rationale and methodology employed to design and integrate various systems onboard. Significant improvisations have been made in the structural design of the vehicle to enhance its hydrodynamic stability and maneuverability to perform discrete tasks in comparison to the previous vehicles developed by the team. The focus is laid on the embedded and power system to enhance reliability, modularity, and power distribution. The software stack is designed to run in decentralized multi-threaded agent architecture, with the threads handling pressure sensor, cameras, control system, IMU, mission planner each performing input and output operations in continuous loops. PID control algorithms achieve the desired dynamic control. The vision system is devised to monitor the marine environment and detect underwater contoured objects.
Index Terms: AUV, Design, Power System, PID, ROS, Vision.
Scope of the Article: Autonomous Robots