Abstract: To improve the path planning ability of Artificial Potential Field (APF) in complex obstacle environments, an improved circulating APF path planning method based on obstacle convexification is proposed. By changing the direction of the repulsive potential field into a circulation around the edge of the obstacle of the APF method, this design solves the problem that the platform may fall into the local minimum when the platform-target line is perpendicular to the obstacle boundary. For the polygonal obstacles (both concave and convex) and circular obstacles, the obstacle convexification methods including the initial obstacle convexification and the iterative convexification for intersection set are given, which transforms the complex obstacle space into the convex obstacle space, avoiding the problem of no solution when the platform entering the concave polygon or concave zone caused by intersecting obstacles. In the simulation environment, the path planning results are compared when adopting the traditional APF method, the circulating APF method without the obstacle convexification, and the circulating APF method using the obstacle convexification. And the time consumptions of different methods are analyzed under different obstacle numbers and intersecting obstacle numbers. The results suggest that the circulating APF method using obstacle convexification can significantly improve the path planning performance under complex obstacle environments. In addition, this method has good real-time performance that the time consumption of single step calculation for every obstacle ranges from 0.02-0.03 ms, enabling the online path planning in complex obstacle environments.

Key words: route planning, artificial potential field, local minimum, obstacle convexification, path planning