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Heading Prediction in Unmanned Ground Vehicles by Laser Compass
November 2009
Mey Khalili, The MITRE Corporation
Richard Weatherly, The MITRE Corporation
Robert Bolling, The MITRE Corporation
Keven Ring, The MITRE Corporation
Bob Grabowski, The MITRE Corporation
Kevin Forbes, The MITRE Corporation
Cindy Cicalese, The MITRE Corporation
ABSTRACT
This paper presents an on-line algorithm which
provides high signal to noise ratio heading predictions for unmanned
ground vehicles. The algorithm uses cross correlation
of SICK laser scans to improve the heading predictions from
GPS. It is tested on our ground vehicles in outdoor urban
environment and verified to provide accurate smooth heading
predictions which help with the accurate localization of the
vehicle.
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