LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.
LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.
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GNSS 受限环境中的 LiDAR 扫描匹配辅助惯性导航系统
DOI：
10.3390/s150716710
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发表时间：
2015-07-10
期刊：
影响因子：
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通讯作者：
Hyyppä J
中科院分区：
文献类型：
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作者：
Tang J;Chen Y;Niu X;Wang L;Chen L;Liu J;Shi C;Hyyppä J
提出了一种将辅助惯性导航系统(INS)与低成本LiDAR相匹配的新扫描，作为GNSS退化或被拒绝的环境中基于GNSS的导航系统的替代方案，例如室内区域、茂密的森林或城市峡谷。在这些领域，基于惯导的航位推算(DR)和同步定位与测绘(SLAM)技术通常作为单独的工具用于估计位置。然而，每个独立系统都存在严重的实施问题。惯导系统的速度、位置和航向角的漂移误差会随着时间的推移而积累，为了保持定位精度，必须进行在线标定。在匹配误差可能显著增加的无特征环境中，SLAM的性能较差。每种独立的定位方法都不能以可接受的精度提供可持续的导航解决方案。本文将INS和LiDAR SLAM两种互补技术通过松耦合的扩展卡尔曼滤波(EKF)集成到一个导航框架中，以发挥各自系统的优势，克服各自的缺点，建立稳定的长期导航过程。在自主研发的无人地面车辆平台NAVIS上进行了静、动态现场试验。结果表明，即使在无特征的室内环境中，该方法也能为长期运行提供厘米级的定位精度。
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.