An improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators

In this article, we present an improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators. Specifically, we not only focused on the position for the manipulator end-effectors but also considered their posture in the course of trajectory planning and obstacle avoidance. We introduced boundaries for Cartesian space components to optimize the attractive field function. Moreover, the manipulator achieved a reasonable speed to move to the target pose, regardless of the difference between the initial pose and target pose. We proved the stability using Lyapunov stability theory by introducing velocity feedforward, when the manipulator moved along a continuous trajectory. Considering the shape of the manipulator joints and obstacles, we set up the collision detection model by projecting the obstacles to link coordinates. In this case, establishing the repulsive field between the nearest points on every joint and obstacles with the closest distance was sufficient for achieving obstacle avoidance for redundant manipulators. The simulation results based on a nine-degree-of-freedom hyper-redundant manipulator, which was designed and made in our laboratory, fully substantiated the efficacy and superiority of the proposed method.

Abstract licence: CC BY

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