Abstract: In order to realize the rapid and non-destructive automatic recognition of corn plants in farmland, an automatic recognition method of corn plants using the simultaneous localization and mapping(SLAM) point cloud was proposed. The Pegasus SLAM100 hand-held scanner was used to collect the point cloud data of the corn field, making full use of the verticality characteristics of corn plants in the SLAM point cloud and the prior texture characteristics of plants in the scanning process, the top of corn plants were automatically extracted, then the density clustering algorithm was used to distinguish corn plants and automatically identify corn plants. The experimental results show that the method can realize the automatic recognition of corn plants, and the recognition rate is 92.53%. The research has good engineering application reference value in the fields of automatic corn plant identification, crop yield estimation, and intelligent agriculture research.