Unified Guidance and Jerk-Level Dynamic Inversion for Accurate Position Control of Hybrid UAVs
By combining rotary- and fixed-wing flight, hybrid uncrewed aerial vehicles (H-UAVs) can uniquely address missions combining long-range aerial transport and precise ground-relative tasks, such as the placement or retrieval of payloads. However, to leverage their full maneuverability, first, the fundamentally different operating modes of rotary- and fixed-wing vehicles need to be unified and second, the system be controlled precisely despite complex aerodynamic effects. This work presents a general and lightweight, cascaded control formulation for such versatile and accurate operation of H-UAVs. First, a novel guidance law unifies ground- and air-relative position control modes typical for the individual flight regimes. Second, we formulate a jerk-level feedback-linearization to accurately track the guidance outputs despite model errors and disturbances. In extensive real flight tests with a tiltwing H-UAV, we demonstrate the versatile allocation of (hybrid) flight states and the overall accuracy enabled by the control system. Position errors remain below 0.5 m (one quarter of the wingspan) in the full flight envelope, including accelerated maneuvers up to 10 ms<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and gusting wind reaching 12 m/s. Finally, the control system demonstrates exploiting hybrid flight for transport-related missions with a precise, in-flight pickup of a payload.
Authors
- Thomas Stastny (ORCID: https://orcid.org/0000-0002-7244-7026)
- Olov Andersson (ORCID: https://orcid.org/0000-0001-7248-1112)
- David Rohr (ORCID: https://orcid.org/0000-0003-1531-4574)
- Nicholas Lawrance (ORCID: https://orcid.org/0000-0003-2167-7427)
- Roland Siegwart (ORCID: https://orcid.org/0000-0002-2760-7983)
Institutions
- ETH Zurich (CH)
Publication Details
- Journal
- IEEE Transactions on Robotics
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1109/tro.2024.3502206
- Citations
- 3
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.75