Abstract

This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi-tionally considered a high level planning problem, can be effectively distributed between different levels of control, al-lowing real-time robot operations in a complex environment. This method has been extended to moving obstacles by using a time-varying artificial patential field. We have applied this obstacle avoidance scheme to robot arm mechanisms and have used a new approach to the general problem of real-time manipulator control. We reformulated the manipulator con-trol problem as direct control of manipulator motion in oper-ational space—the space in which the task is originally described—rather than as control of the task’s corresponding joint space motion obtained only after geometric and kine-matic transformation. Outside the obstacles ’ regions of influ-ence, we caused the end effector to move in a straight line with an upper speed limit. The artificial potential field ap-proach has been extended to collision avoidance for all ma-nipulator links. In addition, a joint space artificial potential field is used to satisfy the manipulator internal joint con-straints. This method has been implemented in the COSMOS system for a PUMA 560 robot. Real-time collision avoidance demonstrations on moving obstacles have been performed by using visual sensing.