Development of a Harvesting End-Effector for Eggplants.

Hayashi, Shigehiko; Ganno, Katsunobu; Ishii, Yukitsugu; Tanaka, Ikuo

doi:10.2525/jshita.13.97

Cited by 11 publications

(5 citation statements)

References 5 publications

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“…In addition, vegetables such as aubergines need to be carefully harvested, and only a cutting method is valid since any plucking technique could damage the plant [48]. Finally, this particular crop was also chosen because there are few research studies on it [30,49,50], and therefore, it offers new opportunities for future work.…”

Section: Introductionmentioning

confidence: 99%

A Design Criterion Based on Shear Energy Consumption for Robotic Harvesting Tools

et al. 2020

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Smart and precise agriculture has increasingly been developed in the last decade, and with that, the idea of optimizing the tools commonly used in this field. One way to improve these devices, particularly cutting tools conceived for harvesting purposes, is to measure the shear energy consumption required for a particular plant. The aim of this research is to establish both a design criterion for cutting grippers and a quantifiable way to evaluate and classify a harvesting tool for a specific crop. This design criterion could help to minimize energy consumption in future harvesting robots, making them more energy-efficient.

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Section: Introductionmentioning

confidence: 99%

A Design Criterion Based on Shear Energy Consumption for Robotic Harvesting Tools

et al. 2020

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“…Hayashi et al [65,66] developed a picking robot for the eggplant cultivated in V-frame, as shown in Figures 31 and 32. This type of robot consists of a five-DOF articulated robotic arm, a vision processing, and a mobile platform.…”

Section: A Picking Robot For V-frame Cultivationmentioning

confidence: 99%

Review of smart robots for fruit and vegetable picking in agriculture

Yang

2022

International Journal of Agricultural and Biological Engineering

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The fruit and vegetable picking has posed a great challenge on the production and markets during the harvest season. Manual picking cannot fully meet the rapid requirements of each market, mainly due to the high labor-intensive and time-consuming tasks, even the aging and shortage of agricultural labor force in recent years. Alternatively, smart robotics can be an efficient solution to increase the planting areas for the markets in combination with changes in cultivation, preservation, and processing technology. However, some improvements still need to be performed on these picking robots. To document the progress in and current status of this field, this study performed a bibliometric analysis. This analysis evaluated the current performance characteristics of various fruit and vegetable picking robots for better prospects in the future. Five perspectives were proposed covering the robotic arms, end effectors, vision systems, picking environments, and picking performance for the large-scale mechanized production of fruits and vegetables in modern agriculture. The current problems of fruit and vegetable picking robots were summarized. Finally, the outlook of the fruit and vegetable picking robots prospected from four aspects: structured environment for fruit planting, the algorithm of recognition and positioning, picking efficiency, and cost-saving picking robots. This study comprehensively assesses the current research status, thus helping researchers steer their projects or locate potential collaborators.

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“…Harvesting end-effector 5 The harvesting end-effector is an important tool to pick up the fruit after the manipulator end reaches the fruit. It was composed of a fruit-grasping mechanism, a size-judging mechanism, and a peduncle-cutting mechanism.…”

Section: System Componentsmentioning

confidence: 99%

Robotic Harvesting System for Eggplants

Hayashi

Ganno

Ishii

et al. 2002

JARQ

Self Cite

100

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The harvesting operation for eggplants is complicated and accounts for a little less than 40% of the total number of working hours. For automating the harvesting operation, an intelligent robot that can emulate the judgment of human labor is necessary. This study was conducted with a view to developing a robotic harvesting system that performs recognition, approach, and picking tasks. In order to accomplish these tasks, 3 essential components were developed. First, a machine vision algorithm combining a color segment operation and a vertical dividing operation was developed. The algorithm could detect the fruit even under different light conditions. Next, a visual feedback fuzzy control model to actuate a manipulator was designed. The control model enabled the manipulator end to approach the fruit from a distance of 300 mm. Furthermore, an end-effector composed of a fruit-grasping mechanism, a size-judging mechanism, and a peduncle-cutting mechanism was developed. It produced enough force for grasping the fruit and cutting the tough peduncle. Finally, the 3 essential components were functionally combined, and a basic harvesting experiment was conducted in the laboratory to evaluate the performance of the system. The system showed a successful harvesting rate of 62.5%, although the end-effector cut the peduncle at a slightly higher position from the fruit base. The execution time for harvesting of an eggplant was 64.1 s.

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Development of a Harvesting End-Effector for Eggplants.

Abstract: A robotic harvesting system, which emulates the fruit recognition, approach, and picking This study showed the great feasibility of automating the basic harvesting motion for eggplants.

Cited by 11 publications

References 5 publications

A Design Criterion Based on Shear Energy Consumption for Robotic Harvesting Tools

A Design Criterion Based on Shear Energy Consumption for Robotic Harvesting Tools

Review of smart robots for fruit and vegetable picking in agriculture

Robotic Harvesting System for Eggplants

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