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Aiming at the problem of autonomous intrarow navigation of orchard vehicles, an intrarow path extraction method based on light detection and ranging (LiDAR) was proposed, and a diversified virtual orchard environment to simulate the intrarow path navigation process and evaluate the performance of path extraction algorithm was constructed. A 2D LiDAR was used to measure orchard trunks during the extraction of intrarow path and median filter was used to weaken the measurement noise. Then an elliptical region of interest (ROI) was designed to extract adjacent tree rows, followed by a twostep tree row segmentation method which classified the data into the left and right tree rows. Finally, the tree line was fitted by the least square method and the center line of the tree row was determined as the navigation path. The virtual orchard environment and LiDAR measurement model were established for the simulation of intrarow navigation. The navigation path was generated based on the simulation measurement data and the vehicle movement was controlled in realtime after using a firstorder digital lowpass filter. In the simulation experiments, the planting deviation of fruit tree was set to be ±20cm, the deviation of trunk diameter was ±3cm, and the measurement error of LiDAR was ±3cm. Experimental results showed that the proposed method can extract the navigation path accurately in the case of vehicle yaw, missing tree and curve tree row. When the yaw angle was not more than 15°, the lateral deviation was not more than 1m, and the missing tree rate was not more than 25%, the lateral deviation between vehicle track and path centerline can be controlled within ±14cm. 