关键词: 误匹配, 回环检测, 激光雷达, 点云配准, SLAM

Abstract: Due to the complex orchard environment, single canopy features, and the diffuse reflection of light caused by leaves, the mapping process of orchard environment is mismatched, which increases the cumulative error of mapping. In order to solve the above problems, a method of constructing orchard environment navigation map based on the fusion of Scan Context and NDT-ICP was proposed. In this method, the Ring key is searched quickly to obtain candidate frames, and the similarity between candidate frames and the current frame is scored. The twostage search algorithm is used to effectively detect the loop and reduce the mismatching in the orchard environment map. At the same time, the point cloud registration method based on the fusion of normal distribution transformation rough registration and iterative nearest point accurate registration was used to reduce the cumulative error of the orchard environmental map. The test results show that in KITTI data set, the loopback number of radius search loopback detection method is 42, and the loopback number of Scan Context loopback detection method is 51, improving the loopback number by 21.4%. The root mean square error of NDT-ICP matching algorithm is 12.86 m, and that of ICP matching algorithm is 15.11 m. In the real orchard environment, the number of loop detection using radius search is 196, and the number of loop detection using Scan Context is 261, which increases by 33.2%. The algorithm can effectively reduce the influence of mismatching and large cumulative error in the process of orchard environmental mapping, meet the demand of highprecision environmental map construction in the orchard environment, and provide technical support for promoting the unmanned operation of the orchard environment.

Key words: mismatch, loop closure detection, LiDAR, point cloud registration, SLAM