Rapid development methodology of agricultural robot navigation system working in GNSS-denied environment

doi:10.1007/s40436-023-00438-0

Advances in Manufacturing ›› 2023, Vol. 11 ›› Issue (4): 601-617.doi: 10.1007/s40436-023-00438-0

Rapid development methodology of agricultural robot navigation system working in GNSS-denied environment

Run-Mao Zhao^1,2, Zheng Zhu¹, Jian-Neng Chen^1,2, Tao-Jie Yu¹, Jun-Jie Ma¹, Guo-Shuai Fan¹, Min Wu^1,3, Pei-Chen Huang⁴

1. School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, People's Republic of China;
2. Key Laboratory of Transplanting Equipment and Technology of Zhejiang, Province, Hangzhou, 310018, People's Republic of China;
3. School of Transportation, Zhejiang Industry Polytechnic College, Shaoxing, 312000, Zhejiang, People's Republic of China;
4. College of Automation, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, People's Republic of China

Received:2022-07-31 Revised:2022-09-25 Published:2023-10-27
Contact: Jian-Neng Chen,E-mail:jiannengchen@zstu.edu.cn E-mail:jiannengchen@zstu.edu.cn
Supported by:
This research is funded by the Agricultural Equipment Department of Jiangsu University (Grant No. NZXB20210106), the National Natural Science Foundation of China (Grant No. 52105284), the Leading Goose Program of Zhejiang Province (Grant No. 2022C02052), the China Agriculture Research System of MOF and MARA and Basic, and the Applied Basic Research Project of Guangzhou Basic Research Program in 2022 (Grant No. 202201011691). We also thank the anonymous reviewers for their critical comments and suggestions for improving the manuscript.

Abstract

Abstract: Robotic autonomous operating systems in global n40avigation satellite system (GNSS)-denied agricultural environments (green houses, feeding farms, and under canopy) have recently become a research hotspot. 3D light detection and ranging (LiDAR) locates the robot depending on environment and has become a popular perception sensor to navigate agricultural robots. A rapid development methodology of a 3D LiDAR-based navigation system for agricultural robots is proposed in this study, which includes: (i) individual plant clustering and its location estimation method (improved Euclidean clustering algorithm); (ii) robot path planning and tracking control method (Lyapunov direct method); (iii) construction of a robot-LiDAR-plant unified virtual simulation environment (combination use of Gazebo and SolidWorks); and (vi) evaluating the accuracy of the navigation system (triple evaluation: virtual simulation test, physical simulation test, and field test). Applying the proposed methodology, a navigation system for a grape field operation robot has been developed. The virtual simulation test, physical simulation test with GNSS as ground truth, and field test with path tracer showed that the robot could travel along the planned path quickly and smoothly. The maximum and mean absolute errors of path tracking are 2.72 cm, 1.02 cm; 3.12 cm, 1.31 cm, respectively, which meet the accuracy requirements of field operations, establishing the effectiveness of the proposed methodology. The proposed methodology has good scalability and can be implemented in a wide variety of field robot, which is promising to shorten the development cycle of agricultural robot navigation system working in GNSS-denied environment.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00438-0

Key words: Agricultural robot, Global navigation satellite system (GNSS)-denied environment, Navigation system, 3D light detection and ranging (LiDAR), Rapid developing, Methodology

Run-Mao Zhao, Zheng Zhu, Jian-Neng Chen, Tao-Jie Yu, Jun-Jie Ma, Guo-Shuai Fan, Min Wu, Pei-Chen Huang. Rapid development methodology of agricultural robot navigation system working in GNSS-denied environment[J]. Advances in Manufacturing, 2023, 11(4): 601-617.

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Rapid development methodology of agricultural robot navigation system working in GNSS-denied environment

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