Design and Experiment of Ordinary Tea Profiling Harvesting Device Based on Light Detection and Ranging Perception

Xiaolong Huan, Min Wu, Xianbing Bian, Jiangming Jia, Chenchen Kang, Chuanyu Wu, Runmao Zhao and Jianneng Chen ()
Additional contact information
Xiaolong Huan: School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
Min Wu: School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
Xianbing Bian: School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
Jiangming Jia: School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
Chenchen Kang: Department of Agricultural and Biological Engineering, The Pennsylvania State University, Biglerville, PA 16802, USA
Chuanyu Wu: School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
Runmao Zhao: School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
Jianneng Chen: School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China

Agriculture, 2024, vol. 14, issue 7, 1-23

Abstract: Due to the complex shape of the tea tree canopy and the large undulation of a tea garden terrain, the quality of fresh tea leaves harvested by existing tea harvesting machines is poor. This study proposed a tea canopy surface profiling method based on 2D LiDAR perception and investigated the extraction and fitting methods of canopy point clouds. Meanwhile, a tea profiling harvester prototype was developed and field tests were conducted. The tea profiling harvesting device adopted a scheme of sectional arrangement of multiple groups of profiling tea harvesting units, and each unit sensed the height information of its own bottom canopy area through 2D LiDAR. A cross-platform communication network was established, enabling point cloud fitting of tea plant surfaces and accurate estimation of cutter profiling height through the RANSAC algorithm. Additionally, a sensing control system with multiple execution units was developed using rapid control prototype technology. The results of field tests showed that the bud leaf integrity rate was 84.64%, the impurity rate was 5.94%, the missing collection rate was 0.30%, and the missing harvesting rate was 0.68%. Furthermore, 89.57% of the harvested tea could be processed into commercial tea, with 88.34% consisting of young tea shoots with one bud and three leaves or fewer. All of these results demonstrated that the proposed device effectively meets the technical standards for machine-harvested tea and the requirements of standard tea processing techniques. Moreover, compared to other commercial tea harvesters, the proposed tea profiling harvesting device demonstrated improved performance in harvesting fresh tea leaves.

Keywords: ordinary tea harvester; profiling; LiDAR; RANSAC; rapid control prototyping (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2077-0472/14/7/1147/pdf (application/pdf)
https://www.mdpi.com/2077-0472/14/7/1147/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:14:y:2024:i:7:p:1147-:d:1435340

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().