This letter presents a point cloud based loop-closure method to correct long-term drifts in Light Detection and Ranging based Simultaneous Localization and Mapping systems. In the method, we formulate each keyframe as a fully-connected graph with nodes representing planes. To detect loop-closures, the proposed method employs geometric restrictions to define a similarity metric to match current keyframe and those in the map. After similarity assessment, the candidate keyframes which comply with the geometric restrictions are further checked out successively by normal constraints of planes, and validated by an improved Iterative Closest Point method. The latter also provides relative pose transformation estimation between the current keyframe and the matched keyframe in the global reference frame. Experimental results demonstrate that the proposed method is able to fulfill fast and reliable loop-closure. To benefit the community by serving a benchmark for loop-closure, the entire system is made open source on GitHub 3 .

中文翻译：

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LiPMatch：基于激光雷达点云平面的环路闭合


这封信提出了一种基于点云的闭环方法，用于纠正基于光检测和测距的同步定位和测绘系统中的长期漂移。在该方法中，我们将每个关键帧表示为一个全连接图，其中节点代表平面。为了检测闭环，所提出的方法采用几何限制来定义相似性度量以匹配当前关键帧和地图中的关键帧。相似度评估后，通过平面法线约束依次检查符合几何限制的候选关键帧，并通过改进的迭代最近点法进行验证。后者还提供当前关键帧和全局参考帧中匹配关键帧之间的相对姿态变换估计。实验结果表明，该方法能够实现快速、可靠的闭环。为了通过提供闭环基准来造福社区，整个系统在 GitHub 3 上开源。