A Novel Path Planning Algorithm Considering the Maximum Deflection Angle of Joint

Abstract

The paper deals with a minimum potential energy algorithm considering the maximum deflection angle of joint (MPE-MDA algorithm) for three key factors including the maximum deflection angle of the joint, the total length of the path, and the minimum distance from obstacles. The algorithm is applied for space obstacle avoidance of hyper-redundant manipulators. On the path-following planning of the hyper-redundant manipulator, the MPE-MDA algorithm equates one link to multiple virtual small links and then derives the relationship between the length of the small links and the deflection angle of the small links. The planned path based on this relationship meets that the deflection angle of the link does not exceed the limited angle. The MPE-MDA algorithm resolves the problem that the traditional algorithm cannot limit the maximum deflection angle of the joint. Besides, the paper checks different paths by changing the step length, the direction of path planning, and other factors, and then selects the optimal path according to the evaluation function. Furthermore, by comparing the simulation results of path-following planning employing the MPE-MDA algorithm and the artificial potential field (APF) method, respectively. It is found that when the manipulator moves along the optimal path planned by the MPE-MDA algorithm, it can not only keep the specified distance from the obstacle but also can satisfy the condition that the deflection angle of the joint never exceeds the limited range, which verifies the reliability and effectiveness of the algorithm.

Keywords

• Deflection angle
• hyper-redundant manipulators
• path-following
• obstacle avoidance
• minimum potential energy