Automatic Obstacle Avoidance Path Planning Method for Unmanned Ground Vehicle Based on Improved Bee Colony Algorithm

In order to solve the problems of low accuracy and long time-consuming of traditional obstacle avoidance path planning methods for unmanned ground vehicle (UGV), an automatic obstacle avoidance path planning method based on improved bee colony algorithm is proposed. Based on the analysis of the working principle of the bee colony algorithm, the differential evolution algorithm is used to improve the local search ability of the bee colony algorithm; the kinematics model of the UGV is constructed, and the improved bee colony algorithm is used to optimize the obstacle avoidance path planning of the UGV. On this basis, the obstacles in the path planning are extracted by the multi-objective optimization algorithm. Finally, the obstacle avoidance path automatic planning of UGV based on improved bee colony algorithm is completed. The simulation results show that the maximum error of the proposed method is about 2%, and the planning time is short, so it has certain research value. (C) 2022 Jordan Journal of Mechanical and Industrial Engineering. All rights reserved