Constraint-based Model Predictive Control for holonomic mobile manipulators

In this paper, a controller based on constrained optimization for tracking problems in mobile manipulation is presented. A Model Predictive Control problem is set and solved online, allowing to deal with dynamic scenarios and unforeseen events. Besides acceleration, velocity and position constraints, collision avoidance constraints for the mobile base and the arm and Field-of-View constraints have been enforced and extended over the prediction horizon. Navigation performance has been improved by including an additional goal, derived from the classical vortex field approach, to the MPC problem. An experimental validation on a KUKA youBot mobile manipulator has been carried out, showing the online applicability of the presented approach.