JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS;
MAR 4 2021.
Web of Science Citations:
Applications involving Unmanned Aerial Vehicles (UAVs) have increasingly required faster and more accurate movements to reduce flight time and to improve efficiency in the obstacle avoidance capability. In this context, this work proposes a nonlinear model predictive control (NMPC) strategy formulated on the Special Euclidean group SE(3) for quadrotor trajectory tracking within cluttered environments with unknown obstacles. The approach considers constraints in the states and inputs, with constant disturbance rejection and capable of executing aggressive maneuvers. The UAV attitude is considered as an optimization variable within the control problem thanks to an algebraic ellipsoidal set approach. As a consequence, the collision check takes the UAV attitude into account, allowing aggressive maneuvers. Numerical experiments under realistic conditions allow evaluating the performance of the proposed approach for the UAV. The tested maneuvers are throwing a narrow gap, passing by a nonconvex obstacle gap, avoiding a convex obstacle, and doing slalom movements. In all cases, uncertainties are considered. The achieved results indicate the advantages of executing aggressive maneuvers. (AU)