3D Cane Cut-Point Data 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 using sensors to determine the three-dimensional position of canes to be cut or retained based on attributes like color, thickness, and bud direction, enabling a cutter to precisely prune canes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated pruning systems are implemented, then productivity and consistency are improved, but the ability to make comprehensive judgments on health status, sun exposure, and ventilation deteriorates
Solution Approach 1:
The comprehensive pruning judgment is segmented into multiple independent sensor measurements: health status sensors, sun exposure sensors, ventilation sensors, and position sensors. Each aspect is measured separately by dedicated sensors, and the results are integrated to form the complete pruning decision, enabling automated systems to replicate human-like comprehensive judgment
Solution Approach 2:
The pruning system is designed as a multi-functional integrated platform that simultaneously performs health assessment, sun exposure measurement, ventilation evaluation, and cut-point determination. This universal system replaces multiple separate judgment functions with a single automated platform that handles all aspects of pruning decision-making
2Manufacturing precision
If multiple attributes are measured for each cane, then manufacturing precision of pruning decisions is improved, but device complexity increases
Solution Approach 1:
Multiple sensors for measuring different attributes (health status, sun exposure, ventilation, position, thickness, bud direction) are merged into a single integrated data acquisition system. The sensors work simultaneously and their data are combined by a centralized processor to determine the optimal cut-point, achieving high pruning precision without proportionally increasing system complexity
Solution Approach 2:
A data processing intermediary layer is introduced that receives raw measurements from multiple sensors, integrates and analyzes the information, and outputs the final cut-point determination. This intermediary layer simplifies the system architecture by providing a clear interface between the complex sensor array and the actuation mechanism
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, for each of one or more canes of the fruit tree, acquiring measurement values concerning two or more attributes, including an attribute having different evaluation criteria depending on a cultivation method of the fruit tree and an attribute having unchanging evaluation criteria irrespective of a cultivation method of the fruit tree (S236), based on sensor data including information indicating a three-dimensional structure of the one or more canes, determining the one or more canes each as a cane to be removed or a cane to be retained based on the measurement values (S240), and generating the cut-point data for each cane determined as a cane to be removed (S300).