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http://dx.doi.org/10.7780/kjrs.2021.37.5.1.21

Method to Improve Localization and Mapping Accuracy on the Urban Road Using GPS, Monocular Camera and HD Map  

Kim, Young-Hun (Department of Geoinformatics, University of Seoul)
Kim, Jae-Myeong (Department of Urban Planning Engineering, Seokyeong University)
Kim, Gi-Chang (Department of Geoinformatics, University of Seoul)
Choi, Yun-Soo (Department of Geoinformatics, University of Seoul)
Publication Information
Korean Journal of Remote Sensing / v.37, no.5_1, 2021 , pp. 1095-1109 More about this Journal
Abstract
The technology used to recognize the location and surroundings of autonomous vehicles is called SLAM. SLAM standsfor Simultaneously Localization and Mapping and hasrecently been actively utilized in research on autonomous vehicles,starting with robotic research. Expensive GPS, INS, LiDAR, RADAR, and Wheel Odometry allow precise magnetic positioning and mapping in centimeters. However, if it can secure similar accuracy as using cheaper Cameras and GPS data, it will contribute to advancing the era of autonomous driving. In this paper, we present a method for converging monocular camera with RTK-enabled GPS data to perform RMSE 33.7 cm localization and mapping on the urban road.
Keywords
Monocular Visual SLAM; GPS(RTK); Graph Optimization; Bundle Adjustment; Bias Error;
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