Path Planning for Mobile Robot Based on Improved Artificial Potential Field Method

In this paper, an improved artificial potential field method is proposed to address the problems of excessive gravitational force, unachievable goal, and falling into concave obstacle regions in path planning for the mobile robot using the conventional artificial potential field method. Firstly, adding a dynamic adjustment coefficient to the gravitational field function of the conventional artificial potential field method to improve the problem of excessive gravitational force in the early stage, and adding the distance parameter to the repulsive field function to refrain from the goal unreachability problem resulted from the presence of obstacles near the goal point. Then, according to the distribution of obstacles, expanding the radius of influence of obstacles and setting a temporary goal point are used to realize the escape of the mobile robot in concave obstacle regions, respectively. Finally, the paths are optimized using B-spline. Simulation experiments are carried out for both the improved artificial potential field method and the conventional artificial potential field method. The results show that the improved artificial potential field method is smoother in path planning compared to the conventional artificial potential field method. It can effectively avoid the concave obstacle regions and complete the path planning.