Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance
Autonomous underwater vehicle inspection in 3D environments presents significant challenges in spatial mapping for obstacle avoidance and motion control. Current solutions rely on either 2D forward-looking sonar or expensive 3D sonar systems. To address these limitations, this study proposes a cost-...
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MDPI AG
2025-05-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/5/943 |
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| author | Hui Zhi Zhixin Zhou Haiteng Wu Zheng Chen Shaohua Tian Yujiong Zhang Yongwei Ruan |
| author_facet | Hui Zhi Zhixin Zhou Haiteng Wu Zheng Chen Shaohua Tian Yujiong Zhang Yongwei Ruan |
| author_sort | Hui Zhi |
| collection | DOAJ |
| description | Autonomous underwater vehicle inspection in 3D environments presents significant challenges in spatial mapping for obstacle avoidance and motion control. Current solutions rely on either 2D forward-looking sonar or expensive 3D sonar systems. To address these limitations, this study proposes a cost-effective 3D reconstruction method using an oscillatory forward-looking sonar with a pan-tilt mechanism that extends perception from a 2D plane to a 75-degree spatial range. Additionally, a polar coordinate-based frontier extraction method for sequential sonar images is introduced that captures more complete contour frontiers. Through bridge pier scanning validation, the system shows a maximum measurement error of 0.203 m. Furthermore, the method is integrated with the Ego-Planner path planning algorithm and nonlinear Model Predictive Control (MPC) algorithm, creating a comprehensive underwater 3D perception, planning, and control system. Gazebo simulations confirm that generated 3D point clouds effectively support the Ego-Planner method. Under localisation errors of 0 m, 0.25 m, and 0.5 m, obstacle avoidance success rates are 100%, 60%, and 30%, respectively, demonstrating the method’s potential for autonomous operations in complex underwater environments. |
| format | Article |
| id | doaj-art-cef53c6c61e649f7ba470447cb4ee1ef |
| institution | OA Journals |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-cef53c6c61e649f7ba470447cb4ee1ef2025-08-20T01:56:24ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-05-0113594310.3390/jmse13050943Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle AvoidanceHui Zhi0Zhixin Zhou1Haiteng Wu2Zheng Chen3Shaohua Tian4Yujiong Zhang5Yongwei Ruan6Ocean College, Zhejiang University, Zhoushan 316021, ChinaZhejiang Key Laboratory of Intelligent Robot for Operation and Maintenance, Hangzhou Shenhao Technology Co., Ltd., Hangzhou 311100, ChinaZhejiang Key Laboratory of Intelligent Robot for Operation and Maintenance, Hangzhou Shenhao Technology Co., Ltd., Hangzhou 311100, ChinaOcean College, Zhejiang University, Zhoushan 316021, ChinaZhejiang Key Laboratory of Intelligent Robot for Operation and Maintenance, Hangzhou Shenhao Technology Co., Ltd., Hangzhou 311100, ChinaState Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, 38 Zheda Road, Hangzhou 310027, ChinaState Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, 38 Zheda Road, Hangzhou 310027, ChinaAutonomous underwater vehicle inspection in 3D environments presents significant challenges in spatial mapping for obstacle avoidance and motion control. Current solutions rely on either 2D forward-looking sonar or expensive 3D sonar systems. To address these limitations, this study proposes a cost-effective 3D reconstruction method using an oscillatory forward-looking sonar with a pan-tilt mechanism that extends perception from a 2D plane to a 75-degree spatial range. Additionally, a polar coordinate-based frontier extraction method for sequential sonar images is introduced that captures more complete contour frontiers. Through bridge pier scanning validation, the system shows a maximum measurement error of 0.203 m. Furthermore, the method is integrated with the Ego-Planner path planning algorithm and nonlinear Model Predictive Control (MPC) algorithm, creating a comprehensive underwater 3D perception, planning, and control system. Gazebo simulations confirm that generated 3D point clouds effectively support the Ego-Planner method. Under localisation errors of 0 m, 0.25 m, and 0.5 m, obstacle avoidance success rates are 100%, 60%, and 30%, respectively, demonstrating the method’s potential for autonomous operations in complex underwater environments.https://www.mdpi.com/2077-1312/13/5/943underwater vehicleoscillatory forward-looking sonar3D reconstructionautonomous obstacle avoidance |
| spellingShingle | Hui Zhi Zhixin Zhou Haiteng Wu Zheng Chen Shaohua Tian Yujiong Zhang Yongwei Ruan Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance Journal of Marine Science and Engineering underwater vehicle oscillatory forward-looking sonar 3D reconstruction autonomous obstacle avoidance |
| title | Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance |
| title_full | Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance |
| title_fullStr | Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance |
| title_full_unstemmed | Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance |
| title_short | Oscillatory Forward-Looking Sonar Based 3D Reconstruction Method for Autonomous Underwater Vehicle Obstacle Avoidance |
| title_sort | oscillatory forward looking sonar based 3d reconstruction method for autonomous underwater vehicle obstacle avoidance |
| topic | underwater vehicle oscillatory forward-looking sonar 3D reconstruction autonomous obstacle avoidance |
| url | https://www.mdpi.com/2077-1312/13/5/943 |
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