An obstacle avoidance strategy for complex obstacles based on artificial potential field method

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