Robot vision tracking with a hierarchical CMAC controller

Abstract

Vision has extensively expanded robots' capabilities, making the robot control problem more complex. To track a target with a robot arm in a three-dimensional space involves the use of precise commands. We propose to insert a hierarchical neurocontroller based on CMAC (cerebellar model articulation controller) networks in a visual servoing loop. This hierarchical structure splits the robot's workspace and assigns different CMAC controllers imposing thus a specialized region CMAC. Compared to a single CMAC with the same number of weights, the neurocontroller's sensitivity and precision is increased. Robot positioning and target tracking with visual feedback can then be done with a better precision.