Abstract
The human can handle objects dexterously by feeding back the signals from tactile receptors. We made a prototype robot hand that has an anthropomorphic elastic skin which contains strain gauges and PVDF films as tactile receptors. This robot hand can detect slip between fingers and the grasped object using PVDF film information. In this paper, we make this robot hand learn outputs of own strain gauges when a slip occured by Neural Network. After learning, robot hand can adapt the grasp force to increasing load force of the grasped object and can prevent slip.
