Integration of Biological Neural Models for the Control of Eye Movements in a Robotic Head

We developed a biologically plausible control algorithm to move the eyes of a six degrees of freedom robotic head in a human-like manner. Our neurocontroller, written with the neural simulator Nengo, integrates different biological neural models of eye movements, such as microsaccades, saccades, vestibular-ocular reflex, smooth pursuit and vergence. The coordination of the movements depends on the stream of sensory information acquired by two silicon retinas used as eyes and by an inertial measurement unit, which serves as a vestibular system. The eye movements generated by our neurocontroller resemble those of humans when exposed to the same visual input. This robotic platform can be used to investigate the most efficient exploration strategies used to extract salient features from either a static or dynamic visual scene. Future research should focus on technical enhancements and model refinements of the system.