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Development of a Grape Cut Point Detection System Using Multi-Cameras for a Grape-Harvesting Robot.

Liangliang Yang¹, Tomoki Noguchi^1,2, Yohei Hoshino¹

¹Laboratory of Bio-Mechatronics, Faculty of Engineering, Kitami Institute of Technology, Koentyo 165, Kitami Shi 090-8507, Hokkaido, Japan.

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|January 8, 2025

Summary

This study introduces an AI-powered robot harvester for grapes, utilizing multi-camera systems and object detection to accurately identify stems and determine optimal cutting points, significantly reducing manual labor needs.

Keywords:

grape-harvesting robot multi-camera system stem detection using semantic segmentation you only look once (YOLO) based grapes detection

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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Area of Science:

Agricultural Engineering
Robotics
Computer Vision

Background:

Grape harvesting is labor-intensive, posing challenges for efficiency and cost.
Automation in agriculture is crucial for addressing labor shortages and improving productivity.

Purpose of the Study:

To develop an automated robot harvester for vine grapes.
To create an AI-driven system for precise stem detection and cut point identification.

Main Methods:

A multi-camera system with a base and hand camera was employed.
Object detection using You Only Look Once (YOLO) for grape identification.
Pixel-level semantic segmentation for accurate stem detection and cut point estimation.

Main Results:

The system achieved high detection accuracy: 98% indoors and 93% outdoors.
Successful integration of the detection system with a grape-harvesting robot.
Demonstrated capability for successful outdoor grape harvesting.

Conclusions:

The proposed AI algorithm and multi-camera system effectively automate grape harvesting.
The developed robot harvester shows significant potential for practical agricultural applications.