ISPRS-Archives The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprs-archives-XLVIII-1-W1-2023-547-2023 V-SLAM ENHANCED INS/GNSS FUSION SCHEME FOR LANE LEVEL VEHICULAR NAVIGATION APPLICATIONS IN DYNAMIC ENVIRONMENT Yeh T.-H. 1 Chiang K.-W. 1 Lu P.-R. 1 Li P.-L. 2 Lin Y.-S. 3 Hsu C.-Y. 3 Dept. of Geomatics, National Cheng Kung University, Tainan, Taiwan High Definition Map Research Center, Dept. of Geomatics, National Cheng Kung University, Tainan, Taiwan Automotive Research & Testing Center, Changhua, Taiwan 25 05 2023 XLVIII-1/W1-2023 547 553 Copyright: © 2023 T.-H. Yeh et al. 2023 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-1-W1-2023/547/2023/isprs-archives-XLVIII-1-W1-2023-547-2023.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-1-W1-2023/547/2023/isprs-archives-XLVIII-1-W1-2023-547-2023.pdf

With the development of different sensors, such as global navigation satellite system (GNSS), inertial measurement unit (IMU), LiDAR, radar and camera, more localization information is available for autonomous vehicular applications. However, each sensor has its limitations in different circumstances. For example, visual Simultaneous Localization and Mapping (SLAM) easily loses tracking in an open sky area where accurate GNSS measurements can be obtained. Sensors can complement each other by integrated their information in a multi-sensor fusion scheme. In this study, we proposed a visual-SLAM enhanced INS/GNSS localization fusion scheme for a high dynamic environment. Oriented FAST and rotated BRIEF (ORB) SLAM are used to pre-process image sequences from monocular camera, rescaled and refreshed after applying GNSS measurements, and convert to position and velocity information, which can provide updates to the system. The performance of the fusion system was verified through two field tests at different speed ranges (about 30–60 km/s), using a reliable reference system as ground-truth to assess the accuracy of the proposed localization fusion scheme. The results indicated that the proposed system could improve the navigation accuracy compared to INS/GNSS integration scheme and achieve which-lane level or even where-in-lane level.