LAPSE:2023.21550
Published Article
LAPSE:2023.21550
A Cloud-Based In-Field Fleet Coordination System for Multiple Operations
Caicong Wu, Zhibo Chen, Dongxu Wang, Bingbing Song, Yajie Liang, Lili Yang, Dionysis D. Bochtis
March 22, 2023
In large-scale arable farming, multiple sequential operations involving multiple machines must be carried out simultaneously due to restrictions of short time windows. However, the coordination and planning of multiple sequential operations is a nontrivial task for farmers, since each operation may have its own set of operational features, e.g., operating width and turning radius. Taking the two sequential operations—hoeing cultivation and seeding—as an example, the seeder has double the width of the hoeing cultivator, and the seeder must remain idle while waiting for the hoeing cultivator to finish two rows before it can commence its seeding operation. A flow-shop working mode can coordinate multiple machines in multiple operations within a field when different operations have different implement widths. To this end, an auto-steering-based collaborative operating system for fleet management (FMCOS) was developed to realize an in-field flow-shop working mode, which is often adopted by the scaled agricultural machinery cooperatives. This paper proposes the structure and composition of the FMCOS, the method of operating strip segmenting, and a new algorithm for strip state updating between successive field operations under an optimal strategy for waiting time conditioning between sequential operations. A simulation model was developed to verify the state-updating algorithm. Then, the prototype system of FMCOS was combined with auto-steering systems on tractors, and the collaborative operating system for the server was integrated. Three field experiments of one operation, two operations, and three operations were carried out to verify the functionality and performance of FMCOS. The results of the experiment showed that the FMCOS could coordinate in-field fleet operations while improving both the job quality and the efficiency of fleet management by adopting the flow-shop working mode.
Keywords
agricultural machinery, auto-steering system, collaborative operating system, field experiment, fleet management, flow-shop, Simulation
Suggested Citation
Wu C, Chen Z, Wang D, Song B, Liang Y, Yang L, Bochtis DD. A Cloud-Based In-Field Fleet Coordination System for Multiple Operations. (2023). LAPSE:2023.21550
Author Affiliations
Wu C: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China; Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture, Beijing 100083, China
Chen Z: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Wang D: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Song B: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Liang Y: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Yang L: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Bochtis DD: Institute for Bio-economy and Agri-technology (IBO), Centre for Research and Technology—Hellas (CERTH), 6th km Charilaou-Thermi Rd, GR 57001 Thermi, Thessaloniki, Greece [ORCID]
Journal Name
Energies
Volume
13
Issue
4
Article Number
E775
Year
2020
Publication Date
2020-02-11
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en13040775, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.21550
This Record
External Link

doi:10.3390/en13040775
Publisher Version
Download
Files
Mar 22, 2023
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
79
Version History
[v1] (Original Submission)
Mar 22, 2023
 
Verified by curator on
Mar 22, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.21550
 
Original Submitter
Auto Uploader for LAPSE
Links to Related Works
Directly Related to This Work
Publisher Version