Trunk Detection Method Based on Fusion of Lidar and Camera Data
Aiming at the limitations and singleness of traditional sensors in tree trunk detection,a new tree trunk detection method based on data fusion between lidar and camera is proposed.Firstly,the depth map was used to process lidar point cloud to remove ground point cloud and cluster the tree trunks point cloud,and set the horizontal and vertical adaptive thresholds in the clustering process to remove excess informa-tion such as walls,weeds and leaves.Then,YOLOv3 algorithm was applied to analyze the camera image,which realized target recognition based on tree trunks feature and returned the detection frame and catego-ry information.Finally,the detection results of two sensors were fused based on IoU to identify the tree trunks and return their three-dimensional information and location information.The field test was carried out with the unmanned lawn mower as the carrier.Experimental results show that tree trunk detection ac-curacy of the proposed data fusion algorithm was about 93.1%,average horizontal and longitudinal errors of the tree trunk positioning were 0.075 m and 0.078 m respectively,which can meet tree trunk detection requirements of the unmanned lawn mower and provide a new method for environment perception of intel-ligent agricultural machinery.
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