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The synergy of human arms and wearable robot systems (e.g. exoskeletons) is enabled by a control algorithm that maximizes the transparency between the two subsystems. The transparency can be improved by integrating the admittance control along with an arm redundancy resolution algorithm. Recent research effort resulted in a new criterion for the human arm redundancy resolution for unconstrained arm motions estimating the swivel angle with prediction errors of less than 5°. The proposed criterion for the arm redundancy resolution defines the mouth as the primary target of the the human hand during unconstrained arm motions in free space. It was postulated based on experimental data analysis that this criterion is based on a neural mechanism directing the hand towards the head for self-feeding. In conjunction with the proposed redundancy resolution criteria a task space admittance control algorithm is introduced based on multiple force sensor inputs obtained at the interface between the human arm and the exoskeleton system. The system performance was evaluated by five healthy subjects performing a peg-in-hole task for three different target locations. The velocities and interaction forces at the upper arm, lower arm, handle and tip were recorded and further used to power exchange between the subject and the device. Results indicated that the proposed control scheme outperforms the purely reactive task space admittance control with energy exchange reduced to 11.22%. Improving the quality of the human control of a wearable robot system may allow the robot to be a natural and transparent extension of the operator's body.
Date of Conference: Aug. 28 2012-Sept. 1 2012