Obstacle avoidance of mobile robots using modified artificial potential field algorithm based on vortex and PID adjustment

Abstract

In recent years, autonomous mobile robot has become a key research direction in academia due to their good application prospects. The ability to autonomously avoid obstacles and reach a preset target point is the basic requirement of an intelligent mobile robot. As a common obstacle avoidance algorithm for mobile robots, artificial potential field algorithm (APF) has defects such as local minima problem and GNRON problem. Aiming at the shortcomings of the traditional APF algorithm, this paper proposes an improved artificial potential field algorithm based on point vortex and PID adjustment. The implementation of the improved algorithm is based on the two following main points. Firstly, an irrotational point vortex flow field is added to the original repulsion field of the obstacle to form a composite potential field. Properties of point vortex are used to provide additional virtual deflection force to the robot to avoid getting stuck. Secondly, aiming at GNRON problem, the strength of vortex and the range of action of the vortex repulsive composite potential field are adjusted in real time by means of PID adjustment. Finally, in order to verify the feasibility of the improved algorithm proposed in this paper, a comparison with the traditional APF algorithm was performed in seven environments with different obstacle layouts. The results show that the improved algorithm can be effectively applied to a variety of obstacle environments. Moreover, the local minimal value problem and GNRON problem of the traditional APF algorithm are successfully solved. The mobile robot can flexibly and efficiently avoid obstacles and reach the end point.