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Design and Test of a Levelling System for a Mobile Safflower Picking Platform.

Authors :
Guo, Hui
Lu, Hao
Gao, Guomin
Wu, Tianlun
Chen, Haiyang
Qiu, Zhaoxin
Source :
Applied Sciences (2076-3417); Apr2023, Vol. 13 Issue 7, p4465, 18p
Publication Year :
2023

Abstract

At this stage, safflower picking is mostly performed manually or semi-manually, the picking method is antiquated and the picking precision is low. In this experimental study, a new attitude tilt levelling system was designed for a safflower-picking robot, which has created a solid foundation for the realization of future safflower-picking machine automation. The mobile platform was simplified as a four-point support, and an automatic levelling control system was designed based on the multi-sensor data collected by a multi-inclination sensor, a multi-pressure sensor, and a displacement sensor. The error range of the levelling of the mobile platform was obtained by MATLAB simulation analysis, the relationship between the inclination of the mobile platform and the displacement of the levelling mechanism was analyzed by coordinate transformation, and the maximum levelling range of the levelling mechanism was analyzed. On this basis, an automatic levelling control system was designed. Finally, the safflower-picking mobile platform was tested, and we concluded that the levelling control system can adjust the inclination angle of the mobile platform to within 0.2° and the levelling time to within 7 s. The design of the automatic levelling control system fills the gap in the field of safflower picking and adopts multi-sensor fusion. Compared with other methods, the collected inclination data is more accurate, the levelling accuracy higher, and the levelling time shorter. The final results show that this experimental study provides a strong basis for the realization of the full-mechanical automation of safflower picking. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
7
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
163038350
Full Text :
https://doi.org/10.3390/app13074465