We contrast the effects of communication latency on our human/robot control technique, called teleassistance, versus traditional teleoperation. In teleassistance, a human operator uses hand signs to guide an otherwise autonomous robot manipulator through a given task. Each sign signals a context switch and provides task-centered reference frames for the robot's autonomous servo-motor routines. The signs are natural, such as pointing to an object to indicate the desire to reach toward it as well as the axis along which to reach. The robot is a Utah/MIT hand mounted on a Puma 760 arm. For both teleassistance and teleoperation, the operator wears an EXOS hand master, a polhemus arm position sensor and a Virtual Research helmet that is coupled to binocular cameras mounted on a second Puma 760. The use of a video helmet allows for remote control of the robot and the simulation of communication lag-time. Experimental results suggest that teleassistance scales well with latency delays, unlike teleoperation.

We present a simple sign language for teleassistance inspired by the work of the Bernstein (1967) and by psychophysical evidence in hand-eye coordination. In our schema, a teleoperator uses hand signs to guide an otherwise autonomous robot manipulator through a given task. Each sign signals a context switch and provides a hand-centered reference frame for the robot's servomotor routines. The signs are natural, such as pointing to an object to indicate the desire to reach toward it as well as the axis along which to reach. These signs are called deictic from the Greek word for pointing to stress their indicative and relative nature. The task example is opening a door using a Utah/MIT hand mounted on a Puma 760 arm. The teleoperator wears an EXOS hand master and polhemus sensor. Three variations of nearest neighbor pattern classification are tested for online recognition of the sign language. The simplest, in which the operator signs each pose once before starting, is the best for this task. The dual-control strategy of teleassistance combines teleoperation and autonomous servo control to their advantage. The use of a symbolic sign language helps to alleviate many problems inherent to literal master/slave teleoperation. Conversely, the integration of global operator guidance and hand-centered coordinate frames permits the servo routines to position the robot in relative coordinates and interpret feedback within a constrained context, significantly simplifying the computation and reducing the need for detailed task models.>