A Discrete-Time Attitude Observer on SO(3) for Vision and GPS Fusion
This addresses drift in attitude estimation for applications like robotics or navigation, but it is incremental as it builds on existing sensor fusion methods.
The paper tackles the problem of attitude estimation drift in monocular vision systems by fusing visual odometry with GPS velocity measurements, resulting in an observer that converges exponentially to the true attitude and recovers orientation even with large initial errors.
This paper proposes a discrete-time geometric attitude observer for fusing monocular vision with GPS velocity measurements. The observer takes the relative transformations obtained from processing monocular images with any visual odometry algorithm and fuses them with GPS velocity measurements. The objectives of this sensor fusion are twofold; first to mitigate the inherent drift of the attitude estimates of the visual odometry, and second, to estimate the orientation directly with respect to the North-East-Down frame. A key contribution of the paper is to present a rigorous stability analysis showing that the attitude estimates of the observer converge exponentially to the true attitude and to provide a lower bound for the convergence rate of the observer. Through experimental studies, we demonstrate that the observer effectively compensates for the inherent drift of the pure monocular vision based attitude estimation and is able to recover the North-East-Down orientation even if it is initialized with a very large attitude error.