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Fixed-wing uncrewed aerial vehicles (UAVs) offer significant performance advantages over rotary-wing UAVs in terms of speed, endurance, and efficiency. Such attributes make these vehicles ideally suited for long-range or high-speed reconnaissance operations and position them as valuable complementary members of a heterogeneous multirobot team. However, these vehicles have traditionally been severely limited with regard to both vertical take-off and landing (VTOL) as well as maneuverability, which greatly restricts their utility in environments characterized by complex obstacle fields (e.g., forests or urban centers). This article describes a set of algorithms and hardware advancements that enable agile fixed-wing UAVs to operate as members of a swarm in complex urban environments. At the core of our approach is a direct nonlinear model predictive control (NMPC) algorithm that is capable of controlling fixed-wing UAVs through aggressive poststall maneuvers. We demonstrate in hardware how our online planning and control technique can enable navigation through tight corridors and in close proximity to obstacles. We also demonstrate how our approach can be combined with onboard stereo vision to enable high-speed flight in unknown environments. Finally, we describe our method for achieving swarm system integration; this includes a gimballed propeller design to facilitate automatic take-off, a precision deep-stall landing capability, multivehicle collision avoidance, and software integration with existing swarm architecture.
Published in: IEEE transactions on field robotics.
Volume 1, pp. 394-423