Abstract
This paper presents a shared control scheme for bi-manual robot-assisted rehabilitation exercises. Using game theory-based techniques, we design control schemes for the haptic devices to provide assistance for the upper limb to complete the rehabilitation task. Suitable cost functions are selected for human and robots to achieve shared assistance during the rehabilitation task. Further, the Nash equilibrium solution to the bi-manual rehabilitation task is presented considering a cooperative game between human and robot. An adaptive input observer is used to estimate the applied human inputs and to solve for the robot's shared control. An iterative algorithm that simultaneously estimate the human control gains and solve for the robot's feedback control is presented. Convergence of the estimated human control gains and calculated robot control gains verify that human-robot collaboration is achieved.
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