UAS, multirotor, relative estimation, multi-sensor, GPS denied navigation
An estimation framework is presented that improves the robustness of GPS-denied state estimation to changing environmental conditions by fusing updates from multiple view-based odometry algorithms. This allows the vehicle to utilize a suite of complementary exteroceptive sensors or sensing modalities. By estimating the vehicle states relative to a local coordinate frame collocated with an odometry keyframe, observability of the relative state is maintained. A description of the general framework is given, as well as the specific equations for a multiplicative extended Kalman filter with a multirotor vehicle. Experimental results are presented that demonstrate the ability of the proposed algorithm to produce accurate and consistent estimates in challenging environments that cause a single-sensor solution to fail.
Original Publication Citation
Koch, D., McLain, T., and Brink, K. Multi-Sensor Robust Relative Estimation Framework for GPS-Denied Multirotor Aircraft, 2016 International Conference on Unmanned Aircraft Systems, pp. 589-597, June 2016, Arlington, Virginia.
BYU ScholarsArchive Citation
McLain, Tim; Koch, Daniel P.; and Brink, Kevin M., "Multi-Sensor Robust Relative Estimation Framework for GPS-Denied Multirotor Aircraft" (2016). All Faculty Publications. 1881.
Ira A. Fulton College of Engineering and Technology
© Copyright 2017 IEEE - All rights reserved. This is the author's submitted version of this article. The definitive version can be found at http://ieeexplore.ieee.org/document/7502619/?reload=true
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