Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control

摘要

The aim of this master thesis is to design a control system based on model predictivecontrol (MPC) with sensor data fusion for obstacle avoidance. Since the amount ofobtained data is larger due to multiple sensors, the required sampling time has to belarger enough in comparison with the calculation time of the optimal problem. Thenit is proposed a simplification of the mobile robot model in order to reduce this optimizationtime.The sensor data fusion technique uses the range information of a laser scanner andthe data of a mono-camera acquired from image processing techniques. In image processingdifferent detection algorithms are proposed such as shape and color detection.Therefore an estimation of the obstacles dimension and distance is explained obtainingaccurate results.Finally a data fusion for obstacle determination is developed in order to use thisinformation in the optimization control problem as a path constraint. The obtainedresults show the mobile robot behavior in trajectories tracking and obstacle avoidanceproblems by comparing two different sampling times. It is concluded that the mobilerobot reaches the final desired position while avoiding the detected obstacles along thetrajectory.