【摘要】 针对固态激光雷达视场小导致建图过程中回环检测困难的问题，提出了一种基于单帧-子地图描述子匹配的回环检测算法。首先，利用前端里程计提供的位姿将若干帧点云拼接得到子地图后获取描述子，并将其位置加入K维树中。其次，对于每一个当前帧，利用K维树搜索候选子地图，依次按照里程计位姿投影至子地图坐标系后获取描述子，以实现描述子旋转、平移不变性。然后，利用二进制描述子进行对齐，并利用掩模方法计算当前帧描述子和子地图描述子的相似度。最后，对于符合条件的回环对，使用CFB-ICP算法进行配准获得回环因子，并执行因子图优化。在公开数据集以及真实室外环境中分别进行实验测试，结果显示此算法在满足实时性的前提下，可以减小长程建图时的累积误差，提高定位与建图精度。更多还原

【Abstract】 Small viewing field of the solid-state LiDAR makes loop closure detection difficult. Therefore, a loop closure detection method based on single frame-submap descriptor matching is proposed. First, to obtain a submap with the pose provided by the front-end odometry, several frames of point clouds are spliced, then the descriptors of the submap are obtained, and their positions are added to the KD tree. Second, for each current frame, the KD tree is used to search candidate submaps, and the descriptor is obtained after projecting to the submap coordinate system according to the pose getting from odometry, so as to realize the rotation and translation invariance of the descriptor. Then, the binary descriptor is used for alignment, and the mask method is used to calculate the similarity between the current frame descriptor and the submap descriptor. Finally, the CFB-ICP algorithm is used to register the qualified loop closure pairs to obtain the loop closure factors, and factor graph optimization is carried out. Experimental tests are carried out in open source data sets and real outdoor environments. The results show that the algorithm can reduce the cumulative error under long-distance operations and improve the accuracy of positioning and mapping under the premise of satisfying real-time performance.更多还原