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INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm

机译:使用混合扫描匹配算法的INS / GPS / LiDAR城市和室内环境综合导航系统

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This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.
机译:本文利用全球定位系统(GPS)和光探测与测距(LiDAR)的互补特性,在不同的环境条件下,对惯性导航系统(INS)进行定期校正。在可获得GPS信号且稀疏的LiDAR测量的开放天空中,GPS与INS集成在一起。同时,在GPS不可靠或不可用且LiDAR测量丰富的受限室外环境和室内,LiDAR取代了GPS以与INS集成。本文还提出了一种创新的混合扫描匹配算法,该算法结合了基于特征的扫描匹配方法和基于迭代最近点(ICP)的扫描匹配方法。该算法可以根据两次扫描中匹配线特征的数量在两种模式之间工作和转换,从而同时实现效率和鲁棒性。并比较了INS和LiDAR混合扫描匹配算法的两种集成方案。在室外和室内环境的无人地面车辆(UGV)上进行了真实的实验。实验结果表明,多传感器集成系统可以在整个轨迹上保持亚米导航精度。

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