Human-machine cooperative telerobotics using uncertain sensor or model data

The promise of automatic and efficient remote operations has fallen short of expectations due to the limited ability of computers to reason and plan in unstructured environments and inadequate sensor accuracy. Our approach is to use available but incomplete and imperfect sensor and model data to augment the operator´s motions, while the operator retains direct control of the manipulator. The amount and type of modification depends not only on the task but also on the accuracy of environmental information from the sensors or model. This form of machine assistance is accomplished by adjusting system parameters which are not under direct control by the operator, specifically, the mapping of positions and velocities between the master and slave. Experimental results from the application of this strategy in an impact task are presented