A neural-network-based flexible assembly controller

Abstract

A neural network-based learning algorithm has been developed for control of robotic peg-in-hole insertions. As simple insertions may comprise up to one-third of all assembly operations, this controller has direct application to automated flexible assembly. A neural network derived from the Cerebellar Model Articulation Controller (CMAC) utilising force feedback from a Cartesian robot is demonstrated.