Abstract
This paper developed a novel shared control scheme for mobile robot based on human surface Electromyo-graphy (sEMG) signals. we combined the human gesture and the stiffness of the arm with the potential field method (PFM) for the mobile robot path planning. On one hand, the sEMG signals are used to recognized the operator's gesture which is applied to control move direction of mobile robots, on the other hand, the stiffness of human arm is estimated that is able to change the velocity of mobile robot. And the PFM is combined with human teleoperation, which can overcame the local minima and goals non-reachable with the obstacle and goal point as the same line with motion direction of mobile robot. The training samples are collected by MYO armband built-in eight bioelectrical sensors used to estimate sEMG signals, and human gesture recognition by Support Vector Machine(SVM). A omnidirectional mobile robot with a depth camera has been teleoperated by the operator, and the results of the experiment presented the effectiveness of the share control scheme.
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