A hybrid PSO-WG algorithm for AUV path planning in unknown oceanic environment

Zheping Yan, Jiyun Li, J. Zou, Juan Li, Rong Zhong
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Abstract

A new path planning algorithm is presented for autonomous underwater vehicle (AUV) in undiscovered ocean environments based on combining particle swarm optimization (PSO) with waypoint guidance (WG). In this algorithm, multi-beams forward looking sonar (FLS) is utilized to discover obstacles, and PSO algorithm is adopted to generate appropriate waypoints, an optimal path with low power consumption and free of collision is generated by following these waypoints. Finally, the simulation experiment is conducted in MATLAB 2015, the simulation results show that this algorithm can generate optimal paths with shorter path length and better smoothness.
未知海洋环境下AUV路径规划的混合PSO-WG算法
提出了一种基于粒子群算法和航路点制导相结合的自主水下航行器(AUV)路径规划算法。该算法利用多波束前视声纳(FLS)发现障碍物,采用粒子群算法生成合适的航路点,沿着这些航路点生成一条低功耗、无碰撞的最优路径。最后,在MATLAB 2015中进行仿真实验,仿真结果表明,该算法能够生成路径长度更短、平滑度更好的最优路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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