LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments

Sensors

Jian Tang²  Yuwei Chen³  Xiaoji Niu²  Li Wang²  Liang Chen¹  Jingbin Liu³  Chuang Shi²  Juha Hyyppä³ 

[1] Department of Navigation and Positioning, Finnish Geospatial Research Institute, Geodeetinrine 2, Kirkkonummi FI-02431, Finland; E-Mail:;GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, Hubei, China; E-Mails:;Department of Remote Sensing and Photogrammetry, Finnish Geospatial Institute, Kirkkonummi FI-02431, Finland; E-Mails:

关键词: LiDAR;    scan matching;    INS;    EKF;    inertial navigation;   

DOI  :  10.3390/s150716710

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.