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GNSS and LiDAR Integrated Navigation Method in Orchards with Intermittent GNSS Dropout

文献类型： 外文期刊

作者： Li, Yilong 1 ; Feng, Qingchun 1 ; Ji, Chao 4 ; Sun, Jiahui 2 ; Sun, Yu 1 ;

作者机构： 1.Xinjiang Agr Univ, Coll Mech & Elect Engn, Urumqi 830025, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing 100097, Peoples R China

3.Beijing Key Lab Intelligent Equipment Technol Agr, Beijing 100097, Peoples R China

4.Xinjiang Acad Agr & Reclamat Sci, Shihezi 832000, Peoples R China

关键词： autonomous navigation; orchard; GNSS/INS integration; LiDAR; agricultural robot

期刊名称：APPLIED SCIENCES-BASEL （ 影响因子：2.5； 五年影响因子：2.7 ）

ISSN：

年卷期： 2024 年 14 卷 8 期

页码：

收录情况： SCI

摘要： Considering the vulnerability of satellite positioning signals to obstruction and interference in orchard environments, this paper investigates a navigation and positioning method based on real-time kinematic global navigation satellite system (RTK-GNSS), inertial navigation system (INS), and light detection and ranging (LiDAR). This method aims to enhance the research and application of autonomous operational equipment in orchards. Firstly, we design and integrate robot vehicles; secondly, we unify the positioning information of GNSS/INS and laser odometer through coordinate system transformation; next, we propose a dynamic switching strategy, whereby the system switches to LiDAR positioning when the GNSS signal is unavailable; and finally, we combine the kinematic model of the robot vehicles with PID and propose a path-tracking control system. The results of the orchard navigation experiment indicate that the maximum lateral deviation of the robotic vehicle during the path-tracking process was 0.35 m, with an average lateral error of 0.1 m. The positioning experiment under satellite signal obstruction shows that compared to the GNSS/INS integrated with adaptive Kalman filtering, the navigation system proposed in this article reduced the average positioning error by 1.6 m.

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