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In order to be able to improve the accuracy and efficiency of the acquisition of three-dimensional information of field crops, taking wheat as the research object, this paper develops a set of field multi-sensor data acquisition device, using a self-propelled vehicle as the mobile carrier and a three-axis gimbal as the stabilisation carrier, and a tightly coupled point cloud acquisition system of LiDAR and IMU was constructed. By studying the imaging characteristics of the sensors and the acquisition method, a laser SLAM-based acquisition method was proposed to construct a high-precision point cloud map in the field, so as to accurately acquire the point cloud information of crops in the field, and be able to complete the construction of the map at a speed of 1.5 m/s, without the need to add additional field targets, which saved the resources for matching the point cloud at a later stage. On the basis of the point cloud map, pre-processing was completed by using straight through filtering, Octree-based downsampling and statistical filtering. An accurate extraction method of ground area based on verticality and height model was proposed. For the difficulty of obtaining the root point cloud during the growth period of wheat, the point cloud PCA analysis was used to calculate the normal vector of the point cloud for the calculation of verticality, and the secondary combination of the height model successfully segmented out the irregular ground points, and the new canopy height model was calculated by using the ground stabilisation fitting plane. Through statistical analysis, compared with the true value of manual measurement, the accuracy of SLAM-based three-dimensional map of wheat in the field, the root mean square error can reach 0.04 m;at the same time, the correlation coefficient between the canopy height extraction algorithm and the true value of manual measurement reached 0.979. The research can provide a powerful tool for the design of the three-dimensional trait collection system and trait analysis of wheat in the field.