Robot vision tracking with a hierarchical CMAC controller

Vision has extensively expanded the robots capabilities, making the robot control problem more complex. To track a target with a robot arm in a three-dimensional space involves to use 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 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.