3D Sensor-Guided Vine Cane Pruning for Automated Selection
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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 unmanned systems.
Innovation Solution
A method and system for generating cut-point data using sensors to determine the three-dimensional position for pruning, involving grouping canes, assessing attributes like color, thickness, and direction, and using a controller to guide a cutter for precise pruning based on these data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive judgment on health status, sun exposure, and ventilation is performed for each cane, then pruning quality and fruit yield are improved, but automation difficulty increases
Solution Approach 1:
The patent segments the pruning decision-making process into distinct evaluation dimensions (health status, sun exposure, ventilation) and processes each separately using dedicated sensors. This allows comprehensive judgment to be achieved through modular sensor units rather than a monolithic complex system, reducing automation difficulty while maintaining pruning quality.
Solution Approach 2:
The patent employs a multi-functional sensor system where a single integrated sensor unit performs multiple measurement functions (color imaging, depth sensing, 3D structure detection) simultaneously. This universal sensor platform evaluates all necessary pruning criteria (health, sun exposure, ventilation) through one system, improving reliability without proportionally increasing device complexity.
2Measurement precision
If multiple attributes (color, thickness, direction, bud size) are measured for each cane, then cane selection accuracy is improved, but measurement time and system complexity increase
Solution Approach 1:
The patent implements continuous measurement and processing of multiple cane attributes during a single pass through the orchard. The sensor system continuously captures color, depth, and 3D structure data while the processing unit continuously evaluates these attributes, enabling multi-attribute measurement without discrete stopping points, thus reducing total measurement time while maintaining high selection accuracy.
Solution Approach 2:
The patent merges multiple measurement functions (color imaging, depth sensing, 3D scanning) into a single integrated sensor unit that captures all necessary attributes simultaneously. This combining of measurement capabilities allows thickness, direction, bud size, and color to be measured in one operation rather than through separate measurement processes, reducing time loss while improving cane selection accuracy.
3Manufacturing precision
If three-dimensional position data is generated for precise cutter control, then pruning precision is improved, but data processing complexity increases
Solution Approach 1:
The patent introduces an intermediary coordinate transformation process that converts complex multi-angle sensor data into simplified three-dimensional position coordinates. This intermediary processing layer acts as a mediator between raw sensor measurements and cutter control commands, reducing data processing complexity while maintaining high pruning precision through standardized coordinate representation.
Solution Approach 2:
The patent replaces complex mechanical positioning systems with optical sensing and computational geometry. Instead of using mechanically complex devices to physically measure and mark three-dimensional positions, the system uses optical sensors to capture spatial data and computationally derives precise position information, reducing overall system complexity while improving pruning precision.
Data Source
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AI summary
A method includes using a computer or computers to receive sensor data of one or more canes of a fruit tree (200), the sensor data being acquired by a sensor or sensors (520), and determining the one or more canes each as a cane to be removed or a cane to be retained based on the sensor data.