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