Quadrotors’ perching on moving inclined surfaces using uncertainty tolerant planner and thrust regulation

Abstract

Quadrotors with the ability to perch on moving inclined surfaces can save energy and extend their travel distance by leveraging ground vehicles. Achieving dynamic perching places high demands on the performance of trajectory planning and tracking control in SE(3). However, in the perching process, uncertainties in target prediction and tracking errors may cause trajectory planning failure. And, independent control of position and attitude is also difficult for underactuated quadrotors. To address these challenges, we first propose a trajectory planner that considers adaptation to uncertainties in target prediction and tracking errors. In the planner, waypoints are optimized using the average coverage of their reachable set over the uncertain target as a criterion. A real-time trajectory planner based on optimized waypoints is developed accordingly. Secondly, thrust regulation is also implemented in the terminal attitude tracking stage. Therefore, positions and velocities can be controlled simultaneously when a quadrotor’s attitudes are commanded to align with surfaces. Extensive simulation experiments demonstrate that our methods can improve the accuracy of terminal states under uncertainties. The success rate is approximately increased by 50% compared to the two-end planner without using thrust regulation. Perching on the rear window of a car is also achieved outdoors to validate the feasibility and practicality of our methods.