On human performance in teleoperation

Recent experimental attempts in building teleoperated master-slave arm manipulators revealed a serious difficulty that goes beyond the better understood issues of control, sufficiency of input information, and data processing. Namely, a human operator has difficulty in interpreting input information and consequently in teleoperation decision-making. The problem becomes more pronounced when the slave arm has to operate in a complex environment where every point of the arm body is subject to potential collision. This paper traces the source of the difficulty to the limitations in human abilities for space orientation and interpretation of geometrical data, and suggests a solution that capitalizes on recent developments in sensor-based motion planning for whole-sensitive robot arms. This results in a hybrid system in which global planning is done by a human operator, whereas local collision-free motion is controlled by an assisting `autopilot´