Sensor-Based Cane Selection and Cut-Point Data for Automated Pruning

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Solution Overview

Problem

Automating pruning work for fruit trees, particularly in vineyards, is challenging due to the need for comprehensive judgments on health status, sun exposure, and ventilation, which are difficult to replicate in automated systems.

Innovation Solution

A method and system for generating cut-point data that includes grouping canes based on sensor data, determining which canes to remove or retain, and controlling a cutter's three-dimensional position using generated data to perform pruning.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated pruning systems are implemented, then productivity is improved, but the ability to make comprehensive judgments on health status, sun exposure, and ventilation deteriorates

Engineering Contradiction:
Improvepruning efficiencyVSAvoidjudgment accuracy
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The pruning decision process is segmented into multiple independent evaluation dimensions: health status assessment, sun exposure analysis, ventilation evaluation, and growth potential determination. Each dimension is evaluated separately by the control unit based on sensor data, allowing comprehensive judgment to be maintained while automating the overall process. This segmentation enables the system to handle complex pruning decisions through structured, modular analysis rather than requiring holistic human-like judgment.

Inventive Principle:
Principle #1Segmentation

2Manufacturing precision

If multiple attributes are measured for each cane, then manufacturing precision is improved, but device complexity increases

Engineering Contradiction:
Improvecane selection accuracyVSAvoidsystem complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The sensor unit is designed as a multi-functional device that simultaneously measures multiple attributes of canes including color, thickness, length, and bud characteristics using integrated sensors. The control unit processes all these measurements through a unified algorithm that evaluates multiple attributes together to determine pruning decisions. This universal approach allows precise cane selection without requiring separate specialized devices for each measurement, thereby maintaining accuracy while managing system complexity.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP4578266A1Method for generating cut point data, system for generating cut point data, and agricultural machine
Publication Date: 2025.07.02 KUBOTA CORP
  • EP4578266A1 patent drawingFigure 1
  • EP4578266A1 patent drawingFigure 2
  • EP4578266A1 patent drawingFigure 3A

AI summary

The invention concerns a method for generating cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off includes, for each of two or more canes of the fruit tree, acquiring a measurement value(s) concerning one or more attributes based on sensor data of the two or more canes (S230), based on the measurement value (s), determining the two or more canes each as a cane to be removed or a cane to be retained, and generating the cut-point data for each cane to be removed. The determining includes classifying each of the two or more canes into a class representing evaluation criteria for an attribute (S244), based on the measurement value, giving the two or more canes different ranks(S246), and determining the two or more canes each as a cane to be removed or a cane to be retained (S248).