A new method for robot path planning based artificial potential field

摘要

The artificial potential field method is used in mobile robot path planning extensively because of its simpleness, high efficiency and smooth path, but it also has its disadvantages. To overcome the shortcomings of the traditional artificial potential field method in mobile robot path planning, this paper analyzes the reasons that lead to the failure in path planning and puts forward an improved method, in which the attractive and repulsive potential field is optimized, also we propose a strategy of potential field filling to escape the GNRON and local minima problems. At last, we introduce regression search to optimize the path. As a result, the mobile robot can find a better and collision-free path to the goal. The simulation result proves the efficient and flexibility of our new APF.