Aiming at the practical requirement of accurately calibrating external parameters of multiple solid-state lidars, a multi-solid-state lidar automatic calibration algorithm based on point cloud registration is proposed. The calibration algorithm consists of three stages: calibration object segmentation, initial registration and precise registration. In the target segmentation stage, a calibration point cloud is made by superimposing multiple frames of non-repetitive scan data, and then radius filtering and voxel down-sampling filtering are used to segment the target point cloud with obvious texture characteristics. In the initial registration stage, key points are extracted by 3D-HARRIS algorithm, and then key points are described by the signature of histogram of orientation (SHOT) feature descriptor, then the sampling consensus algorithm is performed to calculate the corresponding points and complete the initial registration. In the fine registration stage, the iterative closest point (ICP) algorithm performs precise registration to obtain precise external parameter calibration effects. Experiments are conducted on the Bunny rabbit dataset and the data obtained on site. The results show that the performance of the proposed algorithm is better than many existing algorithms under the premise that the average registration error is less than 1mm.