Live Feeling on Movement of an Autonomous Robot Using a Biological Signal

Abstract

Using Khepera Simulator software, we developed an autonomous robot with a simple neural network by applying the skin conductance response of an observer who was watching the movement of the agent. First, we found that the signals were generated when the observer felt that the robot faced a crucial phase, such as hitting a wall. Therefore, we used the signals as errors that were back-propagated to the network in the robot. By questionnaires completed by the observer, the movement of this robot was compared with the movement of two other kinds of robots. In these other two robots, random signals or switch signals, which were turned on at the robot’s crucial phase, were used as errors instead of the skin conductance responses. From the results, we found that the movement of the robot with biological signals was most similar to the movement of something alive in the three kinds of robots. It is thought that applications of biological signals can promote natural interactions between humans and machines.