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2017.
Avoiding undesired human interaction wrenches for estimation in human-robot manipulation tasks
Knowing accurately the kinematic and dynamic parameters of a manipulated object is required for common coordination strategies in physical human-robot interaction. Parameter bias may disturb the human during interaction and bias the recognition of the human motion intention. This work presents a strategy allowing the tracking of human motion and inducing the motions necessary for identification. Such motions are projected in the null space of the partial grasp matrix, relating the human and the robot redundant motion directions, to avoid the disturbance of the human motion. The approach is evaluated in a human-robot object manipulation setting.