Fast and accurate mobile robot control using a cerebellar model in a sensory delayed environment

Abstract

Fast and accurate control of a system exhibiting significant feedback delay is traditionally a difficult problem to solve. In biological systems, it is thought that a part of the brain called the cerebellum overcomes such difficulties. This paper outlines the use of a cerebellar model in the control of a mobile robot. The model is based around Albus's CMAC neural network (1971, 1975), and uses the response of a nondelayed teaching module as a basis for learning. The model was able to produce results comparable to the teacher despite being subjected to severe sensory latency.