Work

Automatic target spraying and field evaluation of unstructured orchard based on millimeter-wave radar

Year: 2025

Type: article

Abstract: • An orchard automatic target sprayer based on millimeter wave radar is designed. • Millimeter-wave radar point cloud can effectively characterize the target canopy information. • “Walking-Sensing-Spraying” automatic target spray system was established. • Automatic target spraying met the control requirements and reduced pesticide application by 36.12 %. Pesticide precision spraying and efficient deposition is an important development direction of smart agriculture. Aiming at the problems of low pesticide spraying efficiency and severe pesticide loss in unstructured orchards in hilly and mountainous areas, this study proposes an automatic target spray control method. A tracked orchard sprayer based on millimeter-wave radar is designed to address these issues. The information transmission between millimeter wave radar, controller and sprayer are realized, and automatic target spray operation of "Walking-Sensing-Spraying" are realized. Based on the improved self-adaptive DBSCAN clustering algorithm, the improved self-adaptive Alpha_Shape algorithm (a surface reconstruction algorithm) and the least squares circle fitting, the three-dimensional reconstruction and parameter extraction of the target canopy were realized. The results showed that the average relative errors of plant height, canopy width and volume after correction were 1.51 %, 1.96 % and 3.24 %, respectively. The maximum absolute error is 9.59 cm, 5.96 cm and 0.22 m 3 . The millimeter-wave radar point cloud can effectively characterize the plant height, canopy width and volume information of the target canopy, and meet the detection accuracy requirements of target spraying. Field experiment results show that the spray coverage under t automatic target spray meets the needs of orchard pest control, the application of pesticides is reduced by 36.12 %, which achieves the purpose of increasing efficiency, reducing application and precise application. Meanwhile, it can also provide methodological reference for other research on automatic target operation and other fields of automatic target spray technology.

Source: Smart Agricultural Technology

DOI: 10.1016/j.atech.2025.100937

Authors: Xing Xu, Jianying Li, Dongying Shen, Jieli Duan, Zhou Yang, Yinlong Jiang

Institutions: South China Agricultural University, Guangzhou Automobile Group (China), Guangdong Ocean University

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $1,770