Body image constructed from motor and tactile images with visual information

This paper proposes a learning model that enables a robot to acquire a body image for parts of its body that are invisible to itself. The model associates spatial perception based on motor experience and motor image with perception based on the activations of touch sensors and tactile image, both of which are supported by visual information. The tactile image can be acquired with the help of the motor image, which is thought to be the basis for spatial perception, because all spatial perceptions originate in motor experiences. Based on the proposed model, a robot estimates invisible hand positions using the Jacobian between the displacement of the joint angles and the optical flow of the hand. When the hand touches one of the invisible tactile sensor units on the face, the robot associates this sensor unit with the estimated hand position. The simulation results show that the spatial arrangement of tactile sensors is successfully acquired by the proposed model.