针对复杂水下环境下的自主水下航行器(autonomous underwater vehicle,AUV)局部路径规划问题,传统动态窗口法(dynamic window approach,DWA)存在复杂障碍物中陷入局部停滞,动态避障性能不佳等问题,本文提出了一种基于DWA与快速随机搜索树(rapid-exploration random tree,RRT)算法融合的路径规划算法.改进的DWA算法速度空间根据整个动态窗口的周期生成,重设了评价函数并结合AUV任务环境引入洋流能耗评价函数;改进的RRT算法在局部已知空间内规划导引点,帮助DWA脱离局部停滞状态并实现更安全的动态避障.将2种算法融合,实现了AUV在复杂水下环境中的局部路径规划.仿真表明,该融合算法能够降低AUV在洋流中的能耗代价,解决了DWA在复杂障碍物中陷入局部停滞的问题,能够安全有效地躲避动态避障物.
Abstract
For the local path planning problem of autonomous underwater vehicle(AUV)in a complex underwater en-vironment,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 gen-erates 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 al-gorithm 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 cur-rents,solve the problem of DWA getting into local stagnation in complex obstacles,and can avoid dynamic obstacles safely and effectively.
维普
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