Biological visuo-motor control of a pneumatic robot arm

Abstract

We are investigating the application of biologically plausible neural architectures to the problem of the controlling movement of a limb in response to visual stimuli. Our approach is inspired by the ability of biological systems to develop highly accurate control strategies for movement by means of associations between random motor actions and the sensory consequences of these acts. This is achieved using information processing algorithms based upon Kohonen’s self-organizing feature map algorithm (SOFM). As a means of enhancing the abilities of this system we have incorporated additional processing stages, the operation of which are based upon strategies that are consistent with neurobiological approaches to the problem of motor control.