Development and Field Evaluation of a Radial Large‐Stroke Adaptive End‐Effector for Continuous Robotic Harvesting of Banana Fruits at Different Stalk Diameters

ABSTRACT Currently, banana post‐harvesting operations generally rely on manual labor, and the farming population is aging seriously, especially in hilly and mountain areas. To address these issues, the study on key technologies for mechanized banana de‐handing based on an automatic feeding system was carried out, and the finite element analysis (FEA) and kinematic characteristic analysis on the de‐handing cutters were conducted. The static analysis of de‐handing cutters showed that the maximum stress is much smaller than the ultimate stress. Therefore, there will be no permanent deformation and no damages to de‐handing cutters during the banana de‐handing process. Based on the findings from FEA and kinematic characteristic analysis, the experiments to assess the self‐adaptive profiling performance and de‐handing performance were carried out by using the banana de‐handing mechanism. The results of self‐adapting profiling experiment showed that the actual profiling accuracies of the ring de‐handing cutters on cylinders with diameters of 60 mm, 70 mm, 80 mm, and 90 mm were 80.80%, 80.99%, 80.90%, and 82.61%, respectively. The deviations from the corresponding theoretical profiling accuracies were 3.73%, 3.54%, 3.63%, and 1.92%, respectively. To evaluate the de‐handing mechanism, the de‐handing success rate, incision quality, and self‐adaptive profiling effect were selected as indicators. From the de‐handing experiments, it was found that the average de‐handing success rate was 77.63%, the average grade of incision quality was 7.61, and the average grade of self‐adaptive profiling effect was 7.70. The results of the simulation analysis and experimental study showed that the de‐handing mechanism has a great stability and reliability and can meet the banana de‐handing needs in the field. Compared with the de‐handing cutters reported previously, the cutter proposed in this study has better profiling and enveloping capabilities for the diameter of the banana stalk, and for the first time, completely realizes the adaptive profiling of the entire stalk by the mechanical cutter, which has significant practical value for de‐handing banana fruits from stalks of different diameters.

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Publication Details

Journal
Journal of Field Robotics
Published
2025-04-14
DOI
https://doi.org/10.1002/rob.22563
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Development and Field Evaluation of a Radial Large‐Stroke Adaptive End‐Effector for Continuous Robotic Harvesting of Banana Fruits at Different Stalk Diameters

Yufei Liu, Jieli Duan, Zichen Huang, Zhou Yang et al.
Journal of Field Robotics
Smart Agriculture and AI
article

Development and Field Evaluation of a Radial Large‐Stroke Adaptive End‐Effector for Continuous Robotic Harvesting of Banana Fruits at Different Stalk Diameters

Yufei Liu, Jieli Duan, Zichen Huang, Zhou Yang, Xiongzhe Han, Yong He, Wenkai Zhang, Jie Guo
article en

Abstract

ABSTRACT Currently, banana post‐harvesting operations generally rely on manual labor, and the farming population is aging seriously, especially in hilly and mountain areas. To address these issues, the study on key technologies for mechanized banana de‐handing based on an automatic feeding system was carried out, and the finite element analysis (FEA) and kinematic characteristic analysis on the de‐handing cutters were conducted. The static analysis of de‐handing cutters showed that the maximum stress is much smaller than the ultimate stress. Therefore, there will be no permanent deformation and no damages to de‐handing cutters during the banana de‐handing process. Based on the findings from FEA and kinematic characteristic analysis, the experiments to assess the self‐adaptive profiling performance and de‐handing performance were carried out by using the banana de‐handing mechanism. The results of self‐adapting profiling experiment showed that the actual profiling accuracies of the ring de‐handing cutters on cylinders with diameters of 60 mm, 70 mm, 80 mm, and 90 mm were 80.80%, 80.99%, 80.90%, and 82.61%, respectively. The deviations from the corresponding theoretical profiling accuracies were 3.73%, 3.54%, 3.63%, and 1.92%, respectively. To evaluate the de‐handing mechanism, the de‐handing success rate, incision quality, and self‐adaptive profiling effect were selected as indicators. From the de‐handing experiments, it was found that the average de‐handing success rate was 77.63%, the average grade of incision quality was 7.61, and the average grade of self‐adaptive profiling effect was 7.70. The results of the simulation analysis and experimental study showed that the de‐handing mechanism has a great stability and reliability and can meet the banana de‐handing needs in the field. Compared with the de‐handing cutters reported previously, the cutter proposed in this study has better profiling and enveloping capabilities for the diameter of the banana stalk, and for the first time, completely realizes the adaptive profiling of the entire stalk by the mechanical cutter, which has significant practical value for de‐handing banana fruits from stalks of different diameters.

Journal of Field RoboticsVol. 42(6)
South China Agricultural University (CN), Kangwon National University (KR), Zhejiang University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Openalex Percentile: Top 95%
Smart Agriculture and AI
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