3D Cane Cut-Point Mapping for Automated Fruit Tree Pruning
Find Innovative SolutionsGenerate Solutions
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, incorporating attributes like color, thickness, and bud direction to optimize pruning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual pruning judgment based on health status, sun exposure, and ventilation is used, then pruning quality and fruit yield are maintained, but automation and unmanned operation cannot be achieved
Solution Approach 1:
The patent replaces manual visual judgment with automated sensor systems including cameras, LIDAR, and other detection devices that capture multi-dimensional data about cane health, sun exposure, and ventilation conditions. This substitution enables unmanned operation while maintaining judgment accuracy through objective measurement rather than subjective human assessment.
Solution Approach 2:
The patent transforms qualitative pruning judgments into quantitative measurements by defining specific evaluation parameters such as cane thickness, color, sun exposure duration, and ventilation coefficients. These parameters are measured by sensors and processed to objectively determine which canes should be retained or removed, replacing subjective human judgment with measurable criteria.
2Manufacturing precision
If comprehensive attributes including color, thickness, and bud direction are measured for each cane, then pruning precision is improved, but system complexity and measurement requirements increase
Solution Approach 1:
The patent divides the pruning evaluation process into distinct measurement segments, each handled by specialized sensors for specific attributes (cameras for color, LIDAR for three-dimensional structure, other sensors for thickness and bud direction). This segmentation allows the system to measure multiple attributes without requiring a single complex sensor system, making the overall system more manageable and maintainable.
Solution Approach 2:
The patent employs a multi-functional sensor system where a single integrated platform performs multiple measurement functions including optical imaging, three-dimensional scanning, and physical property detection. This universal approach reduces the number of separate devices needed while achieving comprehensive cane characterization for precise cut-point positioning.
Data Source
Figure 1
Figure 2
Figure 3A
AI summary
The invention concerns a method for using a computer or computers to generate 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 acquiring information on a cultivation method of the fruit tree (S270), for each of one or more canes of the fruit tree, acquiring a measurement value(s) concerning one or more attributes including an attribute having different evaluation criteria depending on the cultivation method (S234), based on sensor data including information indicating a three-dimensional structure of the one or more canes acquired by a sensor or sensors, determining the one or more canes each as a cane to be removed or a cane to be retained based on the measurement value(s) (S240), and generating the cut-point data for each cane determined as a cane to be removed (S300).