Abstract
This paper describes the development of a system for dexterous telemanipulation and presents the results of tests involving simple manipulation tasks. The user wears an instrumented glove augmented with an arm-grounded haptic feedback apparatus. A linkage attached to the user’s wrist measures gross motions of the arm. The movements of the user are transferred to a two fingered dexterous robot hand mounted on the end of a 4-DOF industrial robot arm. Forces measured at the robot fingers can be transmitted back to the user via the haptic feedback apparatus. The results obtained in block-stacking and object-rolling experiments indicate that the addition of force feedback to the user did not improve the speed of task execution. In fact, in some cases the presence of incomplete force information is detrimental to performance speed compared to no force information. There are indications that the presence of force feedback did aid in task learning.
Neural Networks for Multi-Finger Robot Hand Control
