Robotization of banana de-handing under multi-constraint scenarios: Challenges and future directions

Banana de-handing is an important part of banana post-harvesting operation. The traditional artificial de-handing model has problems such as labor intensity, inaccurate cutting, uneven cutting surface, unstable catching, and damage of banana fruit, etc. The mapping relationship between the characteristic parameters of the movement posture of the cutter and the influencing factors of the contact stress of banana crown cutting in unstructured environments, and the changing rules of the bumping contact stress of complex multi-shaped banana fruit with the physical property parameters of the cushioning material are the theoretical and technical difficulties that urgently need to be solved in the realization of banana mechanical de-handing. The future research (research on the coupling mechanism of visual cognition-mechanism cutting and low-destructive catching method of full-field continuous de-handing of bananas under multi-constraint scenarios) should: (1) create a database of banana crown, obtain the optimal banana crown recognition model, develop a recognition and locating system of the cutting line of banana crown and obtain its spatial location information; (2) establish the discrete element mechanical model of banana crown and the interaction model between banana crown and the cutter, clarify the stress change and the force wave transmission characteristics of the cutting process, construct the multi-objective optimization equation of the cutting performance, obtain the best combination of cutting parameters, and ascertain the mechanisms of synergistic locating and continuous cutting of banana crown; (3) establish the contact mechanical model of banana fruit drop-bump, parse the bumping characteristics between banana fruit and cushioning material, construct mathematical equations to quantitatively assess damage results, and determine the detract catching method of banana fruit that matches the de-handing mode in multi-constraint scenarios. This study showed that the real-time identification and spatial positioning of fruit, the mechanical properties of crown and the optimization of cutting performance, the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing. The current bottleneck problems and future research directions of intelligent banana de-handing were pointed out in this paper, which can provide a theoretical basis for the optimal design of banana de-handing devices and provide technical support for promoting the practical application of intelligent de-handing equipment. • The bottleneck problems currently faced by the development of intelligent banana de-handing were pointed out. • Robotization will be the next wave of mechanization for banana de-handing. • The real-time identification and spatial positioning of fruit, the mechanical properties of crown and the optimization of cutting performance, the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing. • Four suggestions for further research in the robotization of de-handing were proposed.

Authors

Institutions

Publication Details

Journal
Artificial Intelligence in Agriculture
Published
2024-12-22
DOI
https://doi.org/10.1016/j.aiia.2024.12.002
Citations
3
Primary Topic
Banana Cultivation and Research
Type
article
Field-Weighted Citation Impact
1.80
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robotization of banana de-handing under multi-constraint scenarios: Challenges and future directions

Jieli Duan, Manoj Karkee, Zhou Yang, Yong He et al.
3 citations
Artificial Intelligence in Agriculture
Banana Cultivation and Research
1.80
article

Robotization of banana de-handing under multi-constraint scenarios: Challenges and future directions

Jieli Duan, Manoj Karkee, Zhou Yang, Yong He, Jie Guo
article en
3 citations

Abstract

Banana de-handing is an important part of banana post-harvesting operation. The traditional artificial de-handing model has problems such as labor intensity, inaccurate cutting, uneven cutting surface, unstable catching, and damage of banana fruit, etc. The mapping relationship between the characteristic parameters of the movement posture of the cutter and the influencing factors of the contact stress of banana crown cutting in unstructured environments, and the changing rules of the bumping contact stress of complex multi-shaped banana fruit with the physical property parameters of the cushioning material are the theoretical and technical difficulties that urgently need to be solved in the realization of banana mechanical de-handing. The future research (research on the coupling mechanism of visual cognition-mechanism cutting and low-destructive catching method of full-field continuous de-handing of bananas under multi-constraint scenarios) should: (1) create a database of banana crown, obtain the optimal banana crown recognition model, develop a recognition and locating system of the cutting line of banana crown and obtain its spatial location information; (2) establish the discrete element mechanical model of banana crown and the interaction model between banana crown and the cutter, clarify the stress change and the force wave transmission characteristics of the cutting process, construct the multi-objective optimization equation of the cutting performance, obtain the best combination of cutting parameters, and ascertain the mechanisms of synergistic locating and continuous cutting of banana crown; (3) establish the contact mechanical model of banana fruit drop-bump, parse the bumping characteristics between banana fruit and cushioning material, construct mathematical equations to quantitatively assess damage results, and determine the detract catching method of banana fruit that matches the de-handing mode in multi-constraint scenarios. This study showed that the real-time identification and spatial positioning of fruit, the mechanical properties of crown and the optimization of cutting performance, the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing. The current bottleneck problems and future research directions of intelligent banana de-handing were pointed out in this paper, which can provide a theoretical basis for the optimal design of banana de-handing devices and provide technical support for promoting the practical application of intelligent de-handing equipment. • The bottleneck problems currently faced by the development of intelligent banana de-handing were pointed out. • Robotization will be the next wave of mechanization for banana de-handing. • The real-time identification and spatial positioning of fruit, the mechanical properties of crown and the optimization of cutting performance, the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing. • Four suggestions for further research in the robotization of de-handing were proposed.

Artificial Intelligence in AgricultureVol. 15(1)
South China Agricultural University (CN), Washington State University (US), Zhejiang University (CN)
Climate action
Openalex Percentile: Top 12%
Banana Cultivation and Research
1.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.