Vision-Based Air-to-Air Autonomous Landing of Underactuated VTOL UAVs

This article addresses the problem of air-to-air autonomous landing of a small underactuated unmanned aerial vehicle (UAV) on a larger one (carrier) in a noncooperative manner using vision-based state estimation. A Kalman filter-based state estimator reconstructs the state of the carrier relying on a camera mounted on the small UAV (follower). Then, a three-layer hierarchical architecture is proposed. A hybrid automaton based on a quasitime-optimal approach is used at the position layer to ensure a safe and fast landing. An adaptive observer is developed at the velocity layer to track robustly the reference velocity coming from the position layer and to compensate for the lack of information about the carrier acceleration. An attitude planner and a geometric stabilizer are used at the innermost layer. The proposed control architecture outperforms the one developed in a previous work by reducing the time to land up to 59% and increasing the accuracy up to 47%. Experimental tests have been performed to assess the performance of the proposed algorithm in representative scenarios.