REAL-TIME COLLISION AVOIDANCE IN TELEOPERATED WHOLE-SENSITIVE ROBOT ARM MANIPULATORS

In traditional teleoperation systems, the human operator is saddled with two distinct tasks: 1) moving the robot arm to its desired position, and 2) avoiding obstacles that can obstruct the arm motion. The current robot teleoperation research concentrates on providing the operator with as much input information about the task site as possible using, for example, stereo vision or contact force feedback. These methods presume that the operator is capable of planning motion for the entire body of the robot in a cluttered environment. Studies show, however, that the operators, first, cannot address both tasks in real time, and second, are not good at generating collision-free motion in a complex environment. Recent results in sensor-based motion planning suggest that the collision avoidance task can be handled automatically, thus freeing the operator for global control. To this end, it is also proposed to use whole-sensitive arm manipulators whose whole bodies are covered with a sensitive skin sensor to detect nearby objects. The data from the skin is processed by motion planning algorithms, to avoid collisions for the entire arm body in an unknown or time-varving environment. The motion of the operator-controlled master arm is either repeated faithfully by the slave arm, or, to avoid collisions, is used as general guidance. In the latter case the slave arm attempts to be as close as possible to the positions commanded by the operator, without jeopardizing its safety. The result is an efficient, safe and robust hybrid system in which integration of control by the operator and the automatic system is done transparently and in real time.