通过自旋设计扩大无人机感知视野，实现无额外能耗的高效自主飞行。
A Self-Rotating Tri-Rotor UAV for Field of View Expansion and Autonomous Flight
- 无人机通过持续旋转扩展相机与激光雷达的感知视野。
- 在4.8 m/s风速下仍能稳定飞行，最高速度2.0 m/s时轨迹追踪精度高。
- 适合需要广域感知的复杂环境任务，如森林与车库巡检。
无人机感知依赖机载相机和激光雷达，但受限于狭窄视场（FoV）。本文提出自旋三旋翼无人机SPINNER，通过连续旋转运动，在不增加传感器或能耗的情况下显著扩展机载相机与激光雷达的感知视场，提升环境感知效率。SPINNER仅用三个无刷电机实现三维位置与滚转-俯仰姿态的精确控制，通过反扭矩板设计调节旋转速度。针对旋转飞行带来的强耦合、严重非线性与复杂干扰，提出结合非线性模型预测控制（MPC）与增量式非线性动态逆控的扰动补偿控制框架。实验表明，SPINNER在4.8 m/s风速下仍保持飞行鲁棒性，最大速度2.0 m/s时实现高精度轨迹跟踪；在停车场与森林场景测试中，旋转感知机制显著提升视场覆盖范围，增强感知能力。
原文摘要 · Abstract (English)
Unmanned Aerial Vehicles (UAVs) perception relies on onboard sensors like cameras and LiDAR, which are limited by the narrow field of view (FoV). We present Self-Perception INertial Navigation Enabled Rotorcraft (SPINNER), a self-rotating tri-rotor UAV for the FoV expansion and autonomous flight. Without adding extra sensors or energy consumption, SPINNER significantly expands the FoV of onboard camera and LiDAR sensors through continuous spin motion, thereby enhancing environmental perception efficiency. SPINNER achieves full 3-dimensional position and roll--pitch attitude control using only three brushless motors, while adjusting the rotation speed via anti-torque plates design. To address the strong coupling, severe nonlinearity, and complex disturbances induced by spinning flight, we develop a disturbance compensation control framework that combines nonlinear model predictive control (MPC) with incremental nonlinear dynamic inversion. Experimental results demonstrate that SPINNER maintains robust flight under wind disturbances up to 4.8 \,m/s and achieves high-precision trajectory tracking at a maximum speed of 2.0\,m/s. Moreover, tests in parking garages and forests show that the rotational perception mechanism substantially improves FoV coverage and enhances perception capability of SPINNER.
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