Detection and prevention of slip using sensors with different properties embedded in elastic artificial skin on the basis of previous experience

In dexterous robotic manipulation it is essential to control the force exerted by the robot hands while grasping. This paper describes a method by which robot hands can be controlled on the basis of previous experience of slippage of objects held by the hand. We developed an anthropomorphic human scale robot hand equipped with an elastic skin in which two types of sensors are randomly embedded. One of these sensors is a piezoelectric polyvinylidenefluoride (PVDF) film which can be used for the detection of pressure changes. The other is a strain gauge which can measure static pressure. In our system, PDVF films are used to detect slipping, and strain gauges to measure stresses which are caused by normal and shear forces. The stress measured by the strain gauges are used as input data to the neural network which controls the actuators of the robot. Once a slip is detected, the neural network is updated. We show that this system can control the grasp force of the robot hand and adapt it to the weight of the held object. By using this method, it wa shown that robots can hold grasped objects safely.