RTK and INS Fusion Localization based Obstacle Avoidance Path Planning for Robot
Shudan Fu, Meiyan Zhang, Xiaowen Xu, Fengqin Jiang · 2024
In order to solve the problems of non-minimization of obstacle avoidance path and a large amount of path waste in the conventional use of LiDAR obstacle avoidance, a new obstacle avoidance path planning method with RTK and INS fusion positioning is proposed. In this method, the original data of RTK and INS are input respectively, and the more accurate position is obtained through Kalman filter fusion, and the scene map is roughly established, so that the target point is established relative to the current position, which provides an effective pointing for the planning of the robot obstacle avoidance path, and greatly optimizes the path waste generated by the original obstacle avoidance mechanism in the obstacle avoidance process.