The CMAC Neurocontroller for efficient learning in visual servoing
Reda Kara, Abdelhafidh Moualdia, Mounir Bouhedda · 2018 International Conference on Applied Smart Systems (ICASS) · 2018
The use of vision has increased the capabilities of manipulator robots, making the problem of control more complex. Aimaing to pathway a target with a robot arm in Cartesien space involves to use precise commands. We propose a neural controller based on CMAC (Cerebellar Model Articulation Controller) networks in a visual servoing. This new structure splits the robot's workspace and assigns different CMAC controllers imposing thus specialized region CMAC. Then, the neurocontroller's sensitivity and precision is increased compared to a single CMAC with the same number of weights. Consequently, Robot positioning and target tracking with visual feedback can be done with a better precision.