Terminal phase visual position estimation for a tail-sitting vertical takeoff and landing UAV via a Kalman filter

Allen C. Tsai; Peter W. Gibbens; R. Hugh Stone

doi:10.1117/12.733453

10 September 2007 Terminal phase visual position estimation for a tail-sitting vertical takeoff and landing UAV via a Kalman filter

Allen C. Tsai, Peter W. Gibbens, R. Hugh Stone

Author Affiliations +

Proceedings Volume 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision; 67640P (2007) https://doi.org/10.1117/12.733453
Event: Optics East, 2007, Boston, MA, United States

Abstract

Computer vision has been an active field of research for many decades; it has also become widely used for airborne applications in the last decade or two. Much airborne computer vision research has focused on navigation for Unmanned Air Vehicles; this paper presents a method to estimate the full 3D position information of a UAV by integrating visual cues from one single image with data from an Inertial Measurement Unit under the Kalman Filter formulation. Previous work on visual 3D position estimation for UAV landing has been achieved by using 2 or more frames of image data with feature enriched information in the image; however raw vision state estimates are hugely suspect to image noise. This paper uses a rather conventional type of landing pad with visual features extracted for use in the Kalman filter to obtain optimal 3D position estimates. This methodology promises to provide state estimates that are better suited for guidance and control of a UAV. This also promise autonomous landing of UAVs without GPS information to be conducted. The result of this implementation tested with flight images is presented.

Citation Download Citation

Allen C. Tsai, Peter W. Gibbens, and R. Hugh Stone "Terminal phase visual position estimation for a tail-sitting vertical takeoff and landing UAV via a Kalman filter", Proc. SPIE 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision, 67640P (10 September 2007); https://doi.org/10.1117/12.733453

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