Obstacle Avoidance Strategy of Mobile Robot Based on Improved Artificial Potential Field Method

Abstract

When there are obstacles around the target point, the mobile robot cannot reach the target using traditional Artificial Potential Field (APF). Besides, the traditional APF is prone to local oscillation in complex terrain such as three-point collinear or semi-closed obstacles. Aiming at solving the defects of traditional APF, a novel improved APF algorithm named back virtual obstacle setting strategy-APF (BVO-APF) has been proposed in this paper. There are two main advantages of the proposed method. Firstly, by redefining the gravitational function as logarithmic function, the proposed method can make the mobile robot reach the target point when there are obstacles around the target. Secondly, the proposed method can avoid falling into local oscillation for both three-point collinear and semi-closed obstacles. Compare with APF and other improved APF, the feasibility of the algorithm is proved through software simulation and practical application.

Mobile robot based on artificial potential field method Path planning method research

“…The traditional artificial potential field method is plagued by two primary issues: target unreachability and susceptibility to falling into local minima [3] . Target unreachability occurs when the robot experiences reciprocation due to the combined forces of gravity and repulsion during its approach to the target [4] .…”