Rolling 2D Lidar-Based Navigation Line Extraction Method for Modern Orchard Automation

文献类型： 外文期刊

第一作者： Zhou, Yibo

作者： Zhou, Yibo;Wang, Xiaohui;Wang, Zhijing;Yu, Keqiang;Zhao, Yanru;Ye, Yunxiang;Zhu, Fengle;Yu, Keqiang;Zhao, Yanru;Yu, Keqiang;Zhao, Yanru

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关键词： autonomous navigation; modern orchards; rolling 2D lidar; navigation line extraction

期刊名称：AGRONOMY-BASEL （ 影响因子：3.4； 五年影响因子：3.8 ）

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年卷期： 2025 年 15 卷 4 期

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收录情况： SCI

摘要： Autonomous navigation is key to improving efficiency and addressing labor shortages in the fruit industry. Semi-structured orchards, with straight tree rows, dense weeds, thick canopies, and varying light conditions, pose challenges for tree identification and navigation line extraction. Traditional 3D lidars suffer from a narrow vertical FoV, sparse point clouds, and high costs. Furthermore, most lidar-based tree-row-detection algorithms struggle to extract high-quality navigation lines in scenarios with thin trunks and dense foliage occlusion. To address these challenges, we developed a 3D perception system using a servo motor to control the rolling motion of a 2D lidar, constructing 3D point clouds with a wide vertical FoV and high resolution. In addition, a method for trunk feature point extraction and tree row line detection for autonomous navigation has been proposed, based on trunk geometric features and RANSAC. Outdoor tests demonstrate the system's effectiveness. At speeds of 0.2 m/s and 0.5 m/s, the average distance errors are 0.023 m and 0.016 m, respectively, while the average angular errors are 0.272 degrees and 0.146 degrees. This low-cost solution overcomes traditional lidar-based navigation method limitations, making it promising for autonomous navigation in semi-structured orchards.

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