Control and overall system performance of an upper limb exoskeleton, as a wearable robot, is dictated in part by the human machine interface and the implemented control algorithm. The ultimate goal is to develop algorithms so the operator feels as if theexoskeleton is a natural extension the body. The aim of the current research is to compare the system performance of a 7 degree of freedom wearable upper limb exoskeleton (EXO-UL7) using two multi-sensor admittance controllers (1) task space control and (2) joint space control. Multiple force sensors are needed due to the redundancy in the system (7 DOF). This redundancy is explored and a method is developed to calculate a closed form inverse kinematics (IK) solution. The IK solution is used to develop the task space controller. The joint space controller uses the transpose of the jacobian to resolve sensor forces into joint torques. Six subjects performed a peg in hole task. Six targets covered the main part of the device workspace. Velocities and Interaction forces at the upper arm, lower arm, handle and tip were recorded during the experiments. Power exchange between the subject and device was calculated. Task space based control was about 11% lower in mean interaction energy for the peg in hole task compared to joint space control. Task completion time increased with both controllers compared to back-driving the device.

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