AEKF Based 3 D Localization of Road Surface Images with Sparse Low Accuracy GPS Data
This paper presents a technique for localizing road surface images acquired by a downward facing monocular camera on a vehicle with sparse low accuracy Global Positioning System (GPS) readings. Images are collected by reading vehicle speed through on board diagnostics (OBD) such that distance between two neighboring images is constant. The images are then stitched to create the road surface of arbitrary length. Lastly, the three dimensional (3 D) road surface is created and globally corrected by using the GPS and the elevation map as well as the Adaptive Extended Kalman Filter (AEKF) The advantage of this technique is the possible deployment of a sparse low accuracy GPS due to the use of the adaptive version of Extended Kalman Filter (EKF) The proposed technique was used for localization of local roads and highways of 6.9 km total length in Blacksburg, VA. The results of the localization show the reconstructed 3 D differ from the satellite imagery data only by 7.97%
2018 IEEE 88th Vehicular Technology Conference (VTC Fall)