GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban Canyons
Global Navigation Satellite System Real-time Kinematic (GNSS-RTK) is an indispensable source for the absolute positioning of autonomous systems. Unfortunately, the performance of the GNSS-RTK is significantly degraded in urban canyons, due to the notorious multipath and Non-Line-of-Sight (NLOS). On...
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MDPI AG
2022-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/10/5193 |
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| author | Jiachen Zhang Weisong Wen Feng Huang Yongliang Wang Xiaodong Chen Li-Ta Hsu |
| author_facet | Jiachen Zhang Weisong Wen Feng Huang Yongliang Wang Xiaodong Chen Li-Ta Hsu |
| author_sort | Jiachen Zhang |
| collection | DOAJ |
| description | Global Navigation Satellite System Real-time Kinematic (GNSS-RTK) is an indispensable source for the absolute positioning of autonomous systems. Unfortunately, the performance of the GNSS-RTK is significantly degraded in urban canyons, due to the notorious multipath and Non-Line-of-Sight (NLOS). On the contrary, LiDAR/inertial odometry (LIO) can provide locally accurate pose estimation in structured urban scenarios but is subjected to drift over time. Considering their complementarities, GNSS-RTK, adaptively integrated with LIO was proposed in this paper, aiming to realize continuous and accurate global positioning for autonomous systems in urban scenarios. As one of the main contributions, this paper proposes to identify the quality of the GNSS-RTK solution based on the point cloud map incrementally generated by LIO. A smaller mean elevation angle mask of the surrounding point cloud indicates a relatively open area thus the correspondent GNSS-RTK would be reliable. Global factor graph optimization is performed to fuse reliable GNSS-RTK and LIO. Evaluations are performed on datasets collected in typical urban canyons of Hong Kong. With the help of the proposed GNSS-RTK selection strategy, the performance of the GNSS-RTK/LIO integration was significantly improved with the absolute translation error reduced by more than 50%, compared with the conventional integration method where all the GNSS-RTK solutions are used. |
| first_indexed | 2024-03-10T03:22:18Z |
| format | Article |
| id | doaj.art-463bd0004d4740e5984713dee708193c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T03:22:18Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-463bd0004d4740e5984713dee708193c2023-11-23T09:59:00ZengMDPI AGApplied Sciences2076-34172022-05-011210519310.3390/app12105193GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban CanyonsJiachen Zhang0Weisong Wen1Feng Huang2Yongliang Wang3Xiaodong Chen4Li-Ta Hsu5School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, ChinaDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, ChinaDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, ChinaRiemann Laboratory, Huawei Technologies, Xi’an 710075, ChinaSchool of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, ChinaDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, ChinaGlobal Navigation Satellite System Real-time Kinematic (GNSS-RTK) is an indispensable source for the absolute positioning of autonomous systems. Unfortunately, the performance of the GNSS-RTK is significantly degraded in urban canyons, due to the notorious multipath and Non-Line-of-Sight (NLOS). On the contrary, LiDAR/inertial odometry (LIO) can provide locally accurate pose estimation in structured urban scenarios but is subjected to drift over time. Considering their complementarities, GNSS-RTK, adaptively integrated with LIO was proposed in this paper, aiming to realize continuous and accurate global positioning for autonomous systems in urban scenarios. As one of the main contributions, this paper proposes to identify the quality of the GNSS-RTK solution based on the point cloud map incrementally generated by LIO. A smaller mean elevation angle mask of the surrounding point cloud indicates a relatively open area thus the correspondent GNSS-RTK would be reliable. Global factor graph optimization is performed to fuse reliable GNSS-RTK and LIO. Evaluations are performed on datasets collected in typical urban canyons of Hong Kong. With the help of the proposed GNSS-RTK selection strategy, the performance of the GNSS-RTK/LIO integration was significantly improved with the absolute translation error reduced by more than 50%, compared with the conventional integration method where all the GNSS-RTK solutions are used.https://www.mdpi.com/2076-3417/12/10/5193adaptive GNSS-RTK/LIO fusionGNSS-RTK selectionglobally urban positioningfactor graph optimization |
| spellingShingle | Jiachen Zhang Weisong Wen Feng Huang Yongliang Wang Xiaodong Chen Li-Ta Hsu GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban Canyons Applied Sciences adaptive GNSS-RTK/LIO fusion GNSS-RTK selection globally urban positioning factor graph optimization |
| title | GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban Canyons |
| title_full | GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban Canyons |
| title_fullStr | GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban Canyons |
| title_full_unstemmed | GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban Canyons |
| title_short | GNSS-RTK Adaptively Integrated with LiDAR/IMU Odometry for Continuously Global Positioning in Urban Canyons |
| title_sort | gnss rtk adaptively integrated with lidar imu odometry for continuously global positioning in urban canyons |
| topic | adaptive GNSS-RTK/LIO fusion GNSS-RTK selection globally urban positioning factor graph optimization |
| url | https://www.mdpi.com/2076-3417/12/10/5193 |
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