Robust Collision-Free Guidance for Multirotor Aerial Vehicles Under Short-Range Sensors

This paper is concerned with the translational guidance of multirotor aerial vehicles with uncertain dynamics and equipped with short-range detection sensors in a scenario containing disturbances/uncertainties, multiple accelerated obstacles, and velocity constraints. To address this problem, we propose a robust guidance strategy based on the continuous control obstacles method. To handle disturbances and uncertainties, the proposed method tightens the position and velocity admissible sets according to the respective tracking errors. Moreover, a hybrid prescribed-time arbitrary-order differentiator is employed to robustly estimate the obstacles' velocities and accelerations within a prescribed time interval using measurements from a short-range sensor. As a result, the proposed method can fit into the available time for executing an avoidance maneuver upon the detection and tracking of obstacles. Then, we build a set of possible future positions for the obstacles according to their observed velocities and accelerations, and use this set to calculate a position command for the guided vehicle. The proposed method is experimentally evaluated using an augmented-reality setup composed of a Crazyflie quadcopter, motion capture cameras, and virtual obstacles. The results show that the proposed method is viable for real-time implementation and effective in providing collision avoidance and satisfying velocity constraints.