Relative Navigation Approach for Vision-based Aerial GPS-denied Navigation

Authors

Timothy McLain, Mechanical Engineering Department, Brigham Young UniversityFollow
Randal W. Beard, Department of Electrical and Computer Engineering, Brigham Young UniversityFollow
Robert C. Leishman, US AFRL Sensors Directorate, Wright-Patterson AFB

Keywords

GPS-denied navigation Relative navigation Quadrotor Vision-based autonomy

Abstract

GPS-denied aerial flight is a challenging research problem and requires knowledge of complex elements from several distinct disciplines. Additionally, aerial vehicles can present challenging constraints such as stringent payload limits and fast vehicle dynamics. In this paper we propose a new architecture to simplify some of the challenges that constrain GPS-denied aerial flight. At the core, the approach combines visual graph-SLAM with a multiplicative extended Kalman filter. More importantly, for the front end we depart from the common practice of estimating global states and instead keep the position and yaw states of the MEKF relative to the current node in the map. This relative navigation approach provides simple application of sensor measurement updates, intuitive definition of map edges and covariances, and the flexibility of using a globally consistent map when desired. We verify the approach with hardware flight-test results.

Original Publication Citation

Leishman, R., McLain, T., and Beard, R. Relative Navigation Approach for Vision-based Aerial GPS-denied Navigation, Journal of Intelligent and Robotic Systems, vol. 74, no. 1-2, pp. 97-111, April 2014.

BYU ScholarsArchive Citation

McLain, Timothy; Beard, Randal W.; and Leishman, Robert C., "Relative Navigation Approach for Vision-based Aerial GPS-denied Navigation" (2014). Faculty Publications. 1945.
https://scholarsarchive.byu.edu/facpub/1945

Document Type

Peer-Reviewed Article

Publication Date

2014-4

Permanent URL

http://hdl.lib.byu.edu/1877/3898

Publisher

Springer Link

Language

English

College

Ira A. Fulton College of Engineering and Technology

Department

Mechanical Engineering

University Standing at Time of Publication

Full Professor

Copyright Status

© 2017 Springer International Publishing AG. Part of Springer Nature. This is the author's submitted version of this article. The definitive version can be found at https://link.springer.com/article/10.1007/s10846-013-9914-7

Copyright Use Information

http://lib.byu.edu/about/copyright/