Autonomous Exploration Motion Planning Method for Mobile Robot Based on Predicted Paths
Haoyu He, Deyu Tu, Biyong Xu, Shuchao Deng, Baohong Tong, Chenyang Zhang · 2023
Effective and safe autonomous exploration of mobile robots in complex unstructured environments is a challenging research problem. In this paper, we design a predictive motion decision mechanism based on frontier exploration, and then propose a novel motion planning method for autonomous exploration. The autonomous exploration process is decomposed into two stages: the exploration stage and the planning stage. The exploration stage expands the selection of optimal frontier points based on RRT, and the planning stage generates and tracks the optimal frontier points to obtain the most efficient and safe path. An exploration-motion decision mechanism is constructed to regulate the motion speed of the mobile robot and efficiently avoid the local minimum region. Experimental validation shows that the proposed method can safely and stably explore complex unknown scenes and obtain a complete environment grid map.