Avoidability measure in moving obstacle avoidance problem and its use for robot motion planning

Abstract

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept avoidability measure (AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function (VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.