Vision-only Navigation and Control of Unmanned Aerial Vehicles Using the Sigma-Point Kalman Filter

Houwu Bai, Eric Wan, Xubo Song, Andriy Myronenko, and Alexander Bogdanov

Abstract:	This paper presents the vision-only navigation and control of a small autonomous helicopter given only measurements from a video camera fixed on the ground. The goal is to develop an alternative to traditional INS/GPS and on-board vision aided systems. The autonomous navigation and control of the helicopter is achieved using a nonlinear state estimator and a statedependent controller. A key difference to INS/GPS navigation is that measurements of the helicopter’s accelerations and angular velocities are not directly available. The state estimation combines the vision measurements with a dynamic model of the vehicle in a recursive filtering procedure using a Sigma-Point Kalman Filter (SPKF). The estimation of the helicopter’s current state (position, attitude, velocity, and angular velocity) is then fed back in real-time to a state-dependent Riccati equation (SDRE) controller to generate radio control commands to the helicopter. Simulations are provided comparing performance relative to INS/GPS navigation. Experiments also show that an accurate dynamic model of the vehicle is necessary for closed-loop stability. Our results indicate the feasibility of designing a vision-only estimation and control system capable of stabilizing and maneuvering a small unmanned helicopter. Other than simple on-board avionics for low level actuator control, the ground station is responsible for video capture, state-estimation, and state-feedback flight control.
Published in:	Proceedings of the 2007 National Technical Meeting of The Institute of Navigation January 22 - 24, 2007 The Catamaran Resort Hotel San Diego, CA
Pages:	1264 - 1275
Cite this article:	Bai, Houwu, Wan, Eric, Song, Xubo, Myronenko, Andriy, Bogdanov, Alexander, "Vision-only Navigation and Control of Unmanned Aerial Vehicles Using the Sigma-Point Kalman Filter," Proceedings of the 2007 National Technical Meeting of The Institute of Navigation, San Diego, CA, January 2007, pp. 1264-1275.
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