A sensor-based obstacle avoidance for a redundant manipulator using a velocity potential function

Abstract

A new approach based on artificial potential function is proposed for the obstacle avoidance of redundant manipulators. Unlike the so-called "global" path planning method, which requires expensive computations for the path search before the manipulator starts to move, this new approach, called the "local" path planning, searches the path in real-time using the local distance information. Previous use of artificial potential functions has exhibited local minima in some complex environments. This paper proposes a potential function that has no local minima even for a cluttered environment. The proposed potential function has been implemented for the collision avoidance of a redundant robot in simulation. A simulation is demonstrated on an algorithm that prevents collisions with obstacles by calculating the repulsive potential exerted on links, based on the shortest distance to an object.