[1]LI Juan,ZHANG Zihao,ZHANG Honghan.Local path planning for AUV with fusion of DWA and RRT algorithms in a complex environment[J].CAAI Transactions on Intelligent Systems,2024,19(4):961-973.[doi:10.11992/tis.202301009]
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Local path planning for AUV with fusion of DWA and RRT algorithms in a complex environment

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 19 Number of periods: 2024 4 Page number: 961-973 Column: 学术论文—智能系统 Public date: 2024-07-05
Title:
Local path planning for AUV with fusion of DWA and RRT algorithms in a complex environment
Author(s):
LI Juan1; 2;  ZHANG Zihao2;  ZHANG Honghan1; 2
1. School of Intelligent Science and Engineering, Harbin Engineering University, Harbin 150001, China;
2. Key Laboratory of Underwater Robot Technology, Harbin Engineering University, Harbin 150001, China
Keywords:
autonomous underwater vehicles; path planning; dynamic window; rapid-exploration random tree; speed space; evaluation function; underwater environment; dynamic obstacle avoidance
CLC:
TP242
DOI:
10.11992/tis.202301009
Abstract:
For the local path planning problem of autonomous underwater vehicle (AUV) in a complex underwater environment, traditional dynamic window approach(DWA) has the problems of getting into local stagnation in complex obstacles and poor dynamic obstacle avoidance performance, etc. In this paper, we propose a path planning algorithm based on the fusion of DWA and Rapid-exploration random tree(RRT) algorithms. The improved DWA algorithm generates the velocity space based on the whole dynamic window period, resets the evaluation function and introduces the evaluation function of ocean current energy consumption in an AUV mission environment; the improved RRT algorithm plans the guide points in a local known space, which helps DWA to get out of the local stagnation and achieve a safer dynamic obstacle avoidance. The two algorithms are fused to achieve local path planning for AUV in a complex underwater environment. Simulations show that the fusion algorithm can reduce the energy cost of AUV in ocean currents, solve the problem of DWA getting into local stagnation in complex obstacles, and can avoid dynamic obstacles safely and effectively.
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