Orchard and Tree Mapping and Description Using Stereo Vision and Lidar

A novel approach for orchard scanning is proposed that is validated through automatic separation of trees and height measurements. The experiments were done in a real orchard recording data from a moving vehicle, using Lidar and stereo vision. The orchard reconstruction was done using tilt sensor corrected GPS positions interpolated through encoder counts. The accuracy of the reconstruction and tree labelling with tilt correction was compared without tilt correction. The accuracy of the Lidar reconstruction was improved, while the stereo vision depended on the tilt correction. The measured heights were correlated R=0.83 and down to an average of 9cm. The approach is suggested to be used for yield estimation, dynamic control of string thinning cylinders, and variable application of pesticides.