Abstract
We improve the performance of a low-quality GPS data on a UGV through use of multiple low-quality GPS modules on a UGV within line of sight of the UAV. The UGV sends GPS data corrections to the UAV on the basis of the distance from the UAV to the UGV as measured by scaling of a standard image pattern stuck on the UGV. Geolocation of both UGV and UAV are performed through the use of the extended Kalman filter integrating GPS aided INS. The positioning error is reduced by a factor of 2.3 in simulation studies and a factor of 1.6 in experiment when 3 GPS sensors are used on the UGV. This is better than what one can get through pure averaging of the GPS sensors in the presence of noise in measuring the UAV-UGV distance. We show how our exploitation of geometry improves GPS sensor performance as more GPS sensors are used.
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Recommended by Associate Editor Deok Jin Lee
Sunghun Jung received his B.S. degree in 2009 from the University of Minnesota, Twin Cities, and M.S. and Ph.D. degrees from the Purdue University, West Lafayette, in 2010 and 2013, respectively, all in Mechanical Engineering. He was with Samsung SDI until August 2016 when he joined Chodang University. His research interests include control and optimization for autonomous operations of unmanned assets, particularly UAV.
Kartik B. Ariyur received his B.Tech. degree in 1996 from the Indian Institute of Technology, Madras, and M.S. and Ph.D. degrees from the University of California, San Diego, in 1999 and 2002, respectively, all in Mechanical Engineering. He was with Honeywell Laboratories in Minneapolis until August 2008 when he joined Purdue University. His research interests are focused on building autonomy into various systems operating in unstructured or uncertain environments.
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Jung, S., Ariyur, K.B. Compensating UAV GPS data accuracy through use of relative positioning and GPS data of UGV. J Mech Sci Technol 31, 4471–4480 (2017). https://doi.org/10.1007/s12206-017-0847-0
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DOI: https://doi.org/10.1007/s12206-017-0847-0