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.

翻译：无人飞行器（UAV）的感知依赖于摄像头、激光雷达等机载传感器，但这些传感器受限于狭窄的视场。本文提出自感知惯性导航旋翼飞行器——一种用于视场扩展与自主飞行的自旋三旋翼无人机。在不增加额外传感器或能耗的前提下，SPINNER通过持续自旋运动显著扩展了机载摄像头与激光雷达传感器的视场，从而提升了环境感知效率。SPINNER仅利用三个无刷电机即可实现完整的3维位置与滚转-俯仰姿态控制，并通过反扭矩盘设计调节旋转速度。针对自旋飞行引发的强耦合、强非线性和复杂扰动问题，我们开发了一种结合非线性模型预测控制与增量非线性动态逆的扰动补偿控制框架。实验结果表明，SPINNER在高达4.8米/秒的风扰下仍能保持稳健飞行，并在2.0米/秒的最大速度下实现高精度轨迹跟踪。此外，在停车场和森林中的测试显示，旋转感知机制显著改善了SPINNER的视场覆盖范围并增强了其感知能力。