Modeling of Superficial Pain using ANNs

In the environment where human coexists with robot, the problem of safety is very important. But it is difficult to separate the robot from the human in time-domain or space-domain unlike the case of factory automation, so a new concept is needed. One approach is to notice sensory and emotional feeling of human, and in this study "pain" is focused, which is a typical unpleasant feeling when the robot contacts us. In this paper, to design the controller based on the pain, an artificial superficial pain model caused by impact is proposed. This ASPM model consists of mechanical pain model, skin model and gate control by artificial neural networks (ANNs). The proposed ASPM is evaluated by experiments. embedded the pain model and its application to anthropor- phic machine. As most of the pain caused by physical in- teraction between robots and humans is the superficial pain caused by impact damage, we focus on the superficial pain in this paper. Artificial superficial pain model (ASPM) caused by impact is proposed. Based on features of the superficial pain, ASPM is constructed by three blocks; mechanical pain model using two mass system, skin model using elastic model and ANNs based on gate control theory.