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摘要: 激光扫描匹配是利用激光雷达进行导航、定位与地图构建的基础，本文对各类激光扫描匹配方法进行了综述。将现有方法归纳为基于点的扫描匹配方法、基于特征的扫描匹配方法和基于数学特性的扫描匹配方法3类，系统总结了相应类型的常见方法；对典型的算法及其改进算法进行了梳理，并指出了存在的主要问题和发展趋势；介绍了激光扫描匹配方法性能评价和对比的最新研究进展，最后，展望了激光扫描匹配技术未来的研究方向。Abstract: Laser scan matching is a foundation for navigation, localization and mapping using Light Detection and Ranging(LiDAR). Various laser scan matching methods are reviewed in detail in this paper. The existing methods are divided into three categories:point-based scan matching method, feature-based scan matching method and mathematical property-based scan matching method, and the common algorithms of corresponding categories are summarized systematically. The typical algorithms and their improved algorithms are outlined, the main issues and development trends are discussed. Then, the latest research progress of performance evaluation and comparison of laser scan matching methods is introduced. Finally, the future research directions of laser scan matching technology are prospected.
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Key words:
- laser scan matching /
- point cloud registration /
- SLAM /
- LiDAR
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表 1 典型扫描匹配方法的特点
Table 1. Features of typical scan matching methods
特点 ICP类方法 基于特征的方法 NDT类方法 是否需要迭代 需要 非必须 需要 是否需要初值 需要 不需要 需要 收敛域 小 / 大 运行速度 慢 快 较快 能否辅助闭环检测 不能 能 能 鲁棒性 较差 较好 好 精度 高，受离群点和噪声影响较大 低，与特征提取精度有关 较高，与体素尺寸密切相关 适用范围 广 结构化场景 广 
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