A Self-Rotating Tri-Rotor UAV for Field of View Expansion and Autonomous Flight

2026-03-30

AI Summary

This work addresses the limited field of view (FoV) of onboard sensors, which constrains environmental perception for conventional unmanned aerial vehicles. To overcome this limitation, the authors propose SPINNER—a spinning tri-rotor drone that actively expands the FoV of its camera and LiDAR through continuous self-rotation, without requiring additional sensors or increased power consumption. The design innovatively integrates an anti-torque plate with a tri-rotor configuration to achieve full six-degree-of-freedom position and attitude control. A disturbance compensation framework combining nonlinear model predictive control with incremental nonlinear dynamic inversion is employed to enhance robustness. Experimental results demonstrate stable flight under wind disturbances up to 4.8 m/s and trajectory tracking at speeds of 2.0 m/s, with significantly improved FoV coverage and perception performance in both parking lot and forest environments.

Abstract

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.

Problem

• Field of View
• Unmanned Aerial Vehicle
• Environmental Perception
• Sensor Limitation
• Autonomous Flight

Innovation

• self-rotating UAV
• field of view expansion
• nonlinear model predictive control
• incremental nonlinear dynamic inversion
• disturbance compensation