Low-Computational-Cost Edge-Computing Robot System for Fruit Automatic Harvesting Using a Raspberry Pi

In recent decades, the agricultural labor force in developed countries has steadily declined, leading to severe shortages of workers. To address this problem, automating various agricultural tasks has become increasingly urgent. This paper focuses specifically on the robotic automation of fruit harvesting. Existing automated harvesting robot systems have several limitations: They lack flexibility as they target only specific fruits, require large batteries because of high power consumption, which reduces operating times, and incur high costs. To reduce power consumption and overall costs, the proposed system uses a single RGB-D sensor and a Raspberry Pi as its sole computational resource. To ensure flexibility, the system utilizes shared peduncle characteristics among different fruits. After identifying the fruit to be harvested, the system locates the connecting peduncle and determines the target cutting pose. The experimental results indicated an average success rate of 91% and an average time of 12.7 seconds to harvest each fruit.

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Publication Details

Published
2025-02-28
DOI
https://doi.org/10.1109/icm62621.2025.10934912
Primary Topic
Smart Agriculture and AI
Type
article
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article

Low-Computational-Cost Edge-Computing Robot System for Fruit Automatic Harvesting Using a Raspberry Pi

Shinpei Kato, Shogo Arai
Smart Agriculture and AI
article

Low-Computational-Cost Edge-Computing Robot System for Fruit Automatic Harvesting Using a Raspberry Pi

Shinpei Kato, Shogo Arai
article en

Abstract

In recent decades, the agricultural labor force in developed countries has steadily declined, leading to severe shortages of workers. To address this problem, automating various agricultural tasks has become increasingly urgent. This paper focuses specifically on the robotic automation of fruit harvesting. Existing automated harvesting robot systems have several limitations: They lack flexibility as they target only specific fruits, require large batteries because of high power consumption, which reduces operating times, and incur high costs. To reduce power consumption and overall costs, the proposed system uses a single RGB-D sensor and a Raspberry Pi as its sole computational resource. To ensure flexibility, the system utilizes shared peduncle characteristics among different fruits. After identifying the fruit to be harvested, the system locates the connecting peduncle and determines the target cutting pose. The experimental results indicated an average success rate of 91% and an average time of 12.7 seconds to harvest each fruit.

Tokyo University of Science (JP)
Openalex Percentile: Top 96%
Smart Agriculture and AI
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Low-Computational-Cost Edge-Computing Robot System for Fruit Automatic Harvesting Using a Raspberry Pi — Shinpei Kato, Shogo Arai · (2025) | TGRS Research Map | TGRS