Path planning for mobile robot based on improved Artificial Potential Field method in complex environment

Abstract

When the obstacles are large, or the complex environment space is relatively narrow, Artificial Potential Field method(APF)is prone to appear repeated shocks, long time planning and obstacle avoidance of difficulty nearby the large obstacles. This paper presents an adaptive dynamic step length adjustment method based on the APF path planning which is combined with the edge detection method to overcome the proposed defects of APF, achieving mobile robot smooth path planning in the complex environment. Hence it can not only improve APF algorithm convergence speed and the safety of path planning, but at the same time ensure the approximate optimum path. Experiments are carried out by simulation to verify the effectiveness of the afore- mentioned methods.