Max Robotics — Global Service Robot Directory + US Certification

About

Sawa Fuke investigates how robots can develop a sense of self, focusing on the intersection of body representation, cross-modal perception, and motor learning. Her pioneering work addresses one of robotics’ most fundamental challenges: enabling machines to construct an internal model of their own bodies, even for parts they cannot directly see. In her most cited paper (48 citations), Fuke proposed a learning model that allows a robot to build a body image by associating motor and tactile experiences with visual information, effectively giving the robot a form of proprioception. She further explored how visual attention and saliency can drive the formation of cross-modal body representations (32 citations), drawing inspiration from neurophysiological studies of tool-use in primates. Her research also includes a neural model of the ventral intraparietal (VIP) area, simulating head-centered, cross-modal representation of the space immediately around the face. By grounding abstract concepts like self-awareness in computational models, Fuke’s work bridges cognitive science and robotics, offering blueprints for more adaptive, embodied artificial agents.