Affiliation:
1. Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China
Abstract
When performing cooperative search operations underwater, multi-autonomous underwater vehicles formations may encounter array-type obstacles such as gullies and bumps. To safely traverse the obstacle domain, this paper balances convergence time, transformation distance and sensor network power consumption, and proposes a Formation Comprehensive Cost (FCC) model to achieve collision avoidance of the formations. The FCC model is used instead of the fitness function of the genetic algorithm to solve the assignment of capture positions and the improved neural self-organizing map (INSOM) algorithm is proposed to achieve efficient path-planning during the capture process. The simulation experiments in 3D space verify that the proposed scheme can improve the efficiency of robot deployment while ensuring safety.
Funder
Jilin Province Key Science and Technology R&D project
Foundation of Education Bureau of Jilin Province
Marine Defense Innovation Found
Aeronautical Science Foundation of China
National Natural Science Foundation of China
Interdisciplinary integration innovation and cultivation project of Jilin university
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference33 articles.
1. USV collision hazard assessment and track planning algorithm;Chen;Ocean Eng.,2022
2. Cooperative formation control of autonomous underwater vehicles: An overview;Das;Int. J. Autom. Comput.,2016
3. Adaptive learning: A new decentralized reinforcement learning approach for cooperative multiagent systems;Li;IEEE Access,2020
4. Co-operative control of a team of autonomous underwater vehicles in an obstacle-rich environment;Das;J. Mar. Eng. Technol.,2016
5. Heonyoung, L., Yeonsik, K., Jongwon, K., and Changwhan, K. (2009, January 14–17). Formation control of leader following unmanned ground vehicles using nonlinear model predictive control. Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Singapore.
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