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Article

Dynamic Target Hunting Under Autonomous Underwater Vehicle (AUV) Motion Planning Based on Improved Dynamic Window Approach (DWA)

1
Key Laboratory of Underwater Robot Technology, Harbin Engineering University, Harbin 150001, China
2
College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2025, 13(2), 221; https://doi.org/10.3390/jmse13020221
Submission received: 26 December 2024 / Revised: 17 January 2025 / Accepted: 23 January 2025 / Published: 24 January 2025
(This article belongs to the Section Ocean Engineering)

Abstract

A dynamic distributed target hunting method is proposed for the problem of distributed moving target hunting by multiple Autonomous Underwater Vehicles (AUVs). By integrating the improved Dynamic Window Approach (DWA) with the Rapidly-exploring Random Tree (RRT) algorithm and incorporating collision avoidance rules between AUVs into the evaluation system of the DWA, the collision avoidance rules are quantified, and corresponding evaluation functions are established. This allows for the selection of motion trajectories that comply with the collision avoidance rules from the predicted trajectory set, improving the obstacle avoidance capability during AUV motion planning and enhancing the reliability of the target hunting task. The introduction of a consistency algorithm maintains the consistency of the group task information and ensures that the hunting strategy can be adjusted promptly in the event of an AUV failure, allowing the target hunting task to continue. Polynomial regression algorithms are used to predict the moving target’s trajectory. Based on a polygonal hunting formation, the hunting potential points are dynamically allocated, and, finally, each AUV executes distributed motion planning towards the hunting potential points to form the hunting formation. Simulation results show that the proposed method achieves efficient multi-AUV-distributed dynamic target hunting.
Keywords: autonomous underwater vehicle; motion planning; obstacle voidance; target hunting autonomous underwater vehicle; motion planning; obstacle voidance; target hunting

Share and Cite

MDPI and ACS Style

Li, J.; Lu, H.; Zhang, H.; Zhang, Z. Dynamic Target Hunting Under Autonomous Underwater Vehicle (AUV) Motion Planning Based on Improved Dynamic Window Approach (DWA). J. Mar. Sci. Eng. 2025, 13, 221. https://doi.org/10.3390/jmse13020221

AMA Style

Li J, Lu H, Zhang H, Zhang Z. Dynamic Target Hunting Under Autonomous Underwater Vehicle (AUV) Motion Planning Based on Improved Dynamic Window Approach (DWA). Journal of Marine Science and Engineering. 2025; 13(2):221. https://doi.org/10.3390/jmse13020221

Chicago/Turabian Style

Li, Juan, Houtong Lu, Honghan Zhang, and Zihao Zhang. 2025. "Dynamic Target Hunting Under Autonomous Underwater Vehicle (AUV) Motion Planning Based on Improved Dynamic Window Approach (DWA)" Journal of Marine Science and Engineering 13, no. 2: 221. https://doi.org/10.3390/jmse13020221

APA Style

Li, J., Lu, H., Zhang, H., & Zhang, Z. (2025). Dynamic Target Hunting Under Autonomous Underwater Vehicle (AUV) Motion Planning Based on Improved Dynamic Window Approach (DWA). Journal of Marine Science and Engineering, 13(2), 221. https://doi.org/10.3390/jmse13020221

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