LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments
A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Sim...
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MDPI AG
2015-07-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/7/16710 |
| _version_ | 1811263255060938752 |
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| author | Jian Tang Yuwei Chen Xiaoji Niu Li Wang Liang Chen Jingbin Liu Chuang Shi Juha Hyyppä |
| author_facet | Jian Tang Yuwei Chen Xiaoji Niu Li Wang Liang Chen Jingbin Liu Chuang Shi Juha Hyyppä |
| author_sort | Jian Tang |
| collection | DOAJ |
| description | A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies—INS and LiDAR SLAM—into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform—NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment. |
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| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:41:30Z |
| publishDate | 2015-07-01 |
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| record_format | Article |
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| spelling | doaj.art-f7142676bffc4d2b97afe0ca0fcb803c2022-12-22T03:19:05ZengMDPI AGSensors1424-82202015-07-01157167101672810.3390/s150716710s150716710LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied EnvironmentsJian Tang0Yuwei Chen1Xiaoji Niu2Li Wang3Liang Chen4Jingbin Liu5Chuang Shi6Juha Hyyppä7GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, Hubei, ChinaDepartment of Remote Sensing and Photogrammetry, Finnish Geospatial Institute, Kirkkonummi FI-02431, FinlandGNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, Hubei, ChinaGNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, Hubei, ChinaDepartment of Navigation and Positioning, Finnish Geospatial Research Institute, Geodeetinrine 2, Kirkkonummi FI-02431, FinlandDepartment of Remote Sensing and Photogrammetry, Finnish Geospatial Institute, Kirkkonummi FI-02431, FinlandGNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, Hubei, ChinaDepartment of Remote Sensing and Photogrammetry, Finnish Geospatial Institute, Kirkkonummi FI-02431, FinlandA new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies—INS and LiDAR SLAM—into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform—NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.http://www.mdpi.com/1424-8220/15/7/16710LiDARscan matchingINSEKFinertial navigation |
| spellingShingle | Jian Tang Yuwei Chen Xiaoji Niu Li Wang Liang Chen Jingbin Liu Chuang Shi Juha Hyyppä LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments Sensors LiDAR scan matching INS EKF inertial navigation |
| title | LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments |
| title_full | LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments |
| title_fullStr | LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments |
| title_full_unstemmed | LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments |
| title_short | LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments |
| title_sort | lidar scan matching aided inertial navigation system in gnss denied environments |
| topic | LiDAR scan matching INS EKF inertial navigation |
| url | http://www.mdpi.com/1424-8220/15/7/16710 |
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