Research on Obstacle Avoidance of Mobile Robot Based on Improved Artificial Potential Field Method
Ren Gong-chang, Weipeng Guo, Peng Liu · 2021
In order to solve the problem of autonomous obstacle avoidance of mobile robots in static and dynamic environments,on the basis of analyzing the deficiencies of the classic artificial potential field method,by improving the repulsive potential field function and adjusting the gravitational component on the coordinate axis,the problems of target unreachable and local minimum in the obstacle avoidance process are solved respectively.At the same time,considering the impact of the speed of obstacles on the obstacle avoidance of the mobile robot,the relative speed between the two is added to the potential field function,so that the mobile robot can autonomously avoid obstacles in a dynamic environment. Finally,a simulation experiment is conducted on the MATLAB platform. The experimental results show that the mobile robot can avoid obstacles in static and dynamic environments and reach the target position,which verifies the feasibility of the improved algorithm.