A Track-Type Orchard Mower Automatic Line Switching Decision Model Based on Improved DeepLabV3+

Lixing Liu, Pengfei Wang, Jianping Li, Hongjie Liu and Xin Yang ()
Additional contact information
Lixing Liu: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Pengfei Wang: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Jianping Li: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Hongjie Liu: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China
Xin Yang: College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China

Agriculture, 2025, vol. 15, issue 6, 1-24

Abstract: To achieve unmanned line switching operations for a track-type mower in orchards, an automatic line switching decision model based on machine vision has been designed. This model optimizes the structure of the DeepLabV3+ semantic segmentation model, using semantic segmentation data from five stages of the line switching process as the basis for generating navigation paths and adjusting the posture of the track-type mower. The improved model achieved an average accuracy of 91.84% in predicting connected areas of three types of headland environments: freespace, grassland, and leaf. The control system equipped with this model underwent automatic line switching tests for the track-type mower, achieving a success rate of 94% and an average passing time of 12.58 s. The experimental results demonstrate that the improved DeepLabV3+ model exhibits good performance, providing a method for designing automatic line switching control systems for track-type mowers in orchard environments.

Keywords: track-type mower; orchard environment; DeepLabV3+; automatic line switching (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: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/15/6/647/pdf (application/pdf)
https://www.mdpi.com/2077-0472/15/6/647/ (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:15:y:2025:i:6:p:647-:d:1615083

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 ().