In order to solve the problem that the existing ground segmentation methods are inaccurate in the complex road surface and sparse point cloud scene, proposes a ground segmentation algorithm based on concave bag algorithm. This method first generates concave packets according to the lidar point cloud, then selects the ground triangle according to the difference of the points in the triangle surface extracted by rough filtering and the scanning characteristics of the normal vector of the triangle surface, and then accurately extracts the interior points of the ground triangle surface. The ground segmentation can be completed accurately according to the distance from the interior point to the triangle surface. The experimental results show that this method can fully consider the geometric characteristics around the point cloud, and is sensitive to the geometric boundary of the object. It can finely segment small bumps, kerbstones and other small obstacles in the scene with sloping ground.