Bryan B.
Adaptive path-planning for AUVs in dynamic underwater environments using sonar data.
B., Bryan; Hasan, Md Junayed; Kannan, Somasundar; Prabhu, Radhakrishna
Authors
Dr Md Junayed Hasan j.hasan@rgu.ac.uk
Research Fellow A
Dr Somasundar Kannan s.kannan1@rgu.ac.uk
Lecturer
Professor Radhakrishna Prabhu r.prabhu@rgu.ac.uk
Professor
Contributors
Henri Bouma
Editor
Professor Radhakrishna Prabhu r.prabhu@rgu.ac.uk
Editor
Yitzhak Yitzhaky
Editor
Hugo J. Kuijf
Editor
Abstract
This paper presents an innovative approach to path-planning for Autonomous Underwater Vehicles (AUVs) in complex underwater environments, leveraging single-beam sonar data. Recognizing the limitations of traditional sonar systems in providing detailed environmental data, we introduce a method to effectively utilize Ping360 sonar scans for obstacle detection and avoidance. Our research addresses the challenges posed by dynamic underwater currents and obstacle unpredictability, incorporating environmental factors such as water temperature, depth, and salinity to adapt the sonar’s range detection capabilities. We propose a novel algorithm that extends beyond the capabilities of the A* algorithm, considering the underwater currents’ impact on AUV navigation. Our method demonstrates significant improvements in navigational efficiency and safety, offering a robust solution for AUVs operating in uncertain and changing underwater conditions. The paper outlines our experimental setup, algorithmic innovations, and the results of comprehensive simulations conducted in a controlled tank environment, showcasing the potential of our approach in enhancing AUV operational capabilities for defense and security applications.
Citation
B, B., HASAN, M.J., KANNAN, S. and PRABHU, R. 2024. Adaptive path-planning for AUVs in dynamic underwater environments using sonar data. In Bouma, H., Prabhu, R., Yitzhahy, Y. and Kuijf, H.J. (eds.) Advanced materials, biomaterials, and manufacturing technologies for security and defence II: proceedings of the 2024 SPIE Security + defence, 16-20 September 2024, Edinburgh, UK. Proceedings of SPIE, 13206. Bellingham, WA: SPIE [online], paper 1320616. Available from: https://doi.org/10.1117/12.3031644
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 2024 Security + defence |
Start Date | Sep 16, 2024 |
End Date | Sep 20, 2024 |
Acceptance Date | Nov 13, 2023 |
Online Publication Date | Nov 13, 2024 |
Publication Date | Dec 31, 2024 |
Deposit Date | Jan 9, 2025 |
Publicly Available Date | Jan 10, 2025 |
Print ISSN | 0277-786X |
Electronic ISSN | 1996-756X |
Peer Reviewed | Peer Reviewed |
Volume | 13206 |
Article Number | 1320616 |
Series Title | Proceedings of the SPIE |
Series Number | 13206 |
Series ISSN | 0277-786X; 1996-756X |
Book Title | Artificial intelligence for security and defence applications II: proceedings of the 2024 Security + defence, 16-20 September 2024, Edinburgh, UK |
ISBN | 9781510681200 |
DOI | https://doi.org/10.1117/12.3031644 |
Keywords | Autonomous underwater vehicles (AUV); Path-planning algorithms; Sonar data processing; Underwater obstacle avoidance |
Public URL | https://rgu-repository.worktribe.com/output/2656367 |
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Copyright Statement
© 2024 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
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