Heading Prediction in Unmanned Ground Vehicles by Laser Compass

By Mey Khalili , Dr. Richard Weatherly , Robert Bolling , Keven Ring , Dr. Robert Grabowski , Kevin Forbes , Cindy Cicalese

This paper presents an on-line algorithm which provides high signal to noise ratio heading predictions for unmanned ground vehicles.

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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.