An Obstacles Avoidance Algorithm Based on Improved Artificial Potential Field

Abstract

Obstacle avoidance is one of the most important issue in the motion planning and control of robot. There are many algorithms to avoid obstacles, but obstacle avoidance algorithm for manipulator is needed consider not only end effector, but also all links of manipulator. In terms of real-time and speed of all system, the algorithm also should be easy as possible. In this paper, an algorithm based on the improved artificial potential field is proposed to solve the problem of the local optimum. The idea of improvement is to find a path by fitting curve with target point and critical oscillating points. There is also a comparison in this paper with planning a path by tangent line. The conclusion proves that the path is much smoother by the algorithm based on improved artificial potential field in this paper. Furthermore, the problem of judder on the trajectory of traditional artificial potential field is also solved in this paper by an improved repulsive potential field function. Finally, the algorithm is proved by planning a smooth path for obstacle avoidance on manipulator: KinovaGen3 in MATLAB.