In order to solve the problem of vacant domain identification and optimal placement point selection in unstructured environment,an algorithm for vacant domain identification and optimal placement point selection was designed based on 3D point cloud information.Machine vision was used to obtain point cloud information,and unobstructed plane areas were obtained by preprocessing,segmentation,and plane fitting of point cloud information to realize the identification of vacant areas.Then,the alpha shapes edge extraction algorithm combined with the Kd-Tree radius neighborhood search algorithm was used to obtain the placeable area.The best placement points were screened out based on the point cloud density.In the ROS system,the feasibility and rationality of the algorithm were experimentally verified.The results show that the algorithm has a fast running speed,good robustness and high recognition accuracy.