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.

Industrial robots are today separated from human workers by means of safety barriers, that protect humans from the risk of collisions. This separation has a clear negative influence on diffusion of robotic technology in shopfloors. On the other hand the removal of protective barriers gives rise to safety issues, that can be addressed with a combination of approaches, including sensor based reactive control. In this paper a distributed proximity sensor, to be mounted on the links of the manipulator, is presented. The optimal placement of the spots of such sensor is discussed, taking into account detection capabilities and safety enhancement. Experiments developed on an ABB IRB 140 robot using off-the-shelf infrared distance sensors as spots are presented.