Air-to-Air Automatic Landing of Unmanned Aerial Vehicles: A Quasi Time-Optimal Hybrid Strategy

Abstract

It is well known that small electric Unmanned Aerial Vehicles (UAVs) suffer from low endurance problems. A possibility to extend the range of UAV missions could be to have a carrier drone with several lightweight multirotors aboard, which can take-off from and land on it. In this paper the challenging problem of Air-to-Air Automatic Landing (AAAL) of UAVs is solved by developing a strategy that combines a quasi-time optimal feedback and a hybrid logic to ensure a safe and fast landing. Eventually, the proposed algorithm is validated through experimental activities involving the landing of a small quadcopter on a bigger octocopter used as a carrier.

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

“…After presenting the structure of the hierarchical architecture, we develop the control laws within each layer. In presenting the high-level control law (corresponding to the position kinematics), we just recall the main steps of the design since the hybrid QTO logic proposed in [17] is exploited with minor adjustments.…”

“…At the highest level, the control design developed in [17] is employed. In deriving the control law for u v , the position tracking error dynamics with e v ≡ 0 is considered, namely:…”

“…While in our previous work [17] we solved the AAAL with a moving Carrier cooperatively, using a motion capture system to provide the Carrier state to the Follower, in this paper we address the more challenging non-cooperative case in which the Carrier state must be reconstructed onboard the Follower by using a dedicated vision-based relative navigation system. Following a widely adopted paradigm in autonomous systems, navigation and control tasks are kept separate.…”

“…Leveraging the cascade structure of the UAV dynamics, a three-layer architecture is employed to simplify the design of the autonomous landing strategy and of the control law itself. The hierarchical approach allows us to use the hybrid Quasi Time-Optimal (QTO) design presented in [17] as the outer loop controller, which proved effective in solving the landing problem when considering only the UAV kinematics and in the cooperative scenario. At the linear velocity loop level, an adaptive observer-based control law, that outperforms the solution proposed in [17], is employed to compensate for unmodeled dynamics and for the lack of information about the Carrier acceleration, which is required to achieve perfect tracking.…”

“…The hierarchical approach allows us to use the hybrid Quasi Time-Optimal (QTO) design presented in [17] as the outer loop controller, which proved effective in solving the landing problem when considering only the UAV kinematics and in the cooperative scenario. At the linear velocity loop level, an adaptive observer-based control law, that outperforms the solution proposed in [17], is employed to compensate for unmodeled dynamics and for the lack of information about the Carrier acceleration, which is required to achieve perfect tracking. An attitude planner and a geometric stabilizer [18], [19] are used at the innermost level to handle the underactuated nature of vectored-thrust UAVs, such as multirotors, which can deliver the control force only along the positive direction orthogonal to the plane of the rotors.…”