Visual Based Predictive Control for a Six Degrees of Freedom Robot

A visual servoing architecture for a six degrees of freedom PUMA robot, using predictive control, is presented. Two different approaches, GPC and MPC, are used. A comparison between these two ones and the classical PI controller is performed. The implemented PUMA robot model simulator used as platform for the development of the control algorithms is presented. A control law based on features extracted from camera images is used. Simulation results show that the proposed strategies provide an efficient control system and that visual servoing architectures using predictive control are faster than those using PI control. Experimental results are obtained from an architecture using a XPC Target and Matlab Simulink. Through this technology is possible to create an operative system which allows working in real time robot control.