A vision based relative navigation framework for formation flight

Unmanned aerial vehicle (UAV) formation flight can vastly increase operational range and persistence through autonomous aerial refuelling or efficient flight on a wingman's wake vortices. Differencing individual UAV state estimates is not sufficiently accurate for close formation operations and...

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Bibliographic Details
Published in2014 IEEE International Conference on Robotics and Automation (ICRA) pp. 4988 - 4995
Main Authors Wilson, Daniel B., Goktogan, Ali H., Sukkarieh, Salah
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2014
Subjects
Algorithm design and analysis
Atmospheric modeling
Global Positioning System
Mathematical model
Quaternions
Visualization
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Summary:Unmanned aerial vehicle (UAV) formation flight can vastly increase operational range and persistence through autonomous aerial refuelling or efficient flight on a wingman's wake vortices. Differencing individual UAV state estimates is not sufficiently accurate for close formation operations and must be augmented with vehicle-to-vehicle observations. To this end, we propose a quaternion based unscented Kalman filter to fuse information from each UAV sensor suite with relative vision observations. The result is a vastly improved relative state estimate that is resilient to brief vision dropouts and degrades gracefully during extended dropouts. Simulated formation flight results validate the approach and provide a numerical analysis of the algorithm performance. Ground based experiments demonstrate the algorithm running in real-time on a dual-UAV system. This represents a significant step towards an airborne implementation.
ISSN:1050-4729
2577-087X
DOI:10.1109/ICRA.2014.6907590