%0 Journal Article %A 冯超 %A 李海明 %A 李庆华 %A 王佳慧 %T HQD-RRT*: a high-quality path planner for mobile robot in dynamic environment %D 2022 %R 10.19682/j.cnki.1005-8885.2022.1007 %J 中国邮电高校学报(英文版) %P 69-80 %V 29 %N 3 %X

Mobile robots have been used for many industrial scenarios which can realize automated manufacturing process instead of human workers. To improve the quality of the optimal rapidly-exploring random tree ( RRT* ) for planning path in dynamic environment, a high-quality dynamic rapidly-exploring random tree ( HQD-RRT* ) algorithm is proposed in this paper, which generates a high-quality solution with optimal path length in dynamic environment. This method proceeds in two stages: initial path generation and path re-planning. Firstly, the initial path is generated by an improved smart rapidly-exploring random tree ( RRT* -SMART) algorithm, and the state tree information is stored as prior knowledge. During the process of path execution, a strategy of obstacle avoidance is proposed to avoid moving obstacles. The cost and smoothness of path are considered to re-plan the initial path to improve the path quality in this strategy. Compared with related work, a higher-quality path in dynamic

environment can be achieved in this paper. HQD-RRT* algorithm can obtain an optimal path with better stability. Simulations on the static and dynamic environment are conducted to clarify the efficiency of HQD-RRT* in avoiding unknown obstacles.

%U https://jcupt.bupt.edu.cn/CN/10.19682/j.cnki.1005-8885.2022.1007