Agricultural Vehicle Guidance Quality via Crop Row Boundary Consistency
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Solution Overview
Problem
Agricultural sprayers face challenges in accurately determining crop row locations due to inconsistent image data, leading to misalignment of nozzles and vehicle positioning, which affects guidance quality during field operations.
Innovation Solution
A system and method utilizing an imaging device and controller to capture and analyze image data, determining a guidance line and crop row boundary consistency parameter, and initiating control actions based on a quality metric to ensure accurate vehicle guidance relative to crop rows, including adjusting image data processing and using location sensors when image quality is poor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image data is used to determine crop row locations, then guidance line determination is enabled, but measurement precision deteriorates when image quality is poor (high weed coverage, variable crop health)
Solution Approach 1:
The system calculates a quality metric for the guidance line based on crop row boundary consistency parameters derived from image data. When the quality metric falls below a threshold, the system provides feedback to switch from image-based guidance to GPS-based guidance, ensuring reliable operation under varying image quality conditions
Solution Approach 2:
The patent introduces an intermediary quality metric evaluation step between image data capture and guidance line determination. This intermediary assesses crop row boundary consistency and determines whether image data is suitable for accurate guidance, acting as a mediator that selects the appropriate guidance data source
2Measurement precision
If multiple image processing parameters are analyzed to improve guidance accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent segments the guidance system into distinct functional modules: image data acquisition, crop row boundary consistency parameter calculation, quality metric determination, and guidance line generation. This segmentation allows each module to perform its specific function independently, managing complexity through modular design
Solution Approach 2:
The system extracts only the essential crop row boundary consistency parameters from the image data that are necessary for quality assessment. By taking out only the relevant features needed for guidance quality determination, the system avoids processing unnecessary data while maintaining measurement precision
Data Source
AI summary
A system for determining agricultural vehicle guidance quality includes an imaging device configured to capture image data depicting a plurality of crops rows present within a field as an agricultural vehicle travels across the field. Additionally, the system includes a controller communicatively coupled to the imaging device. As such, the controller configured to determine a guidance line for guiding the agricultural vehicle relative to the plurality of crop rows based on the captured image data. Furthermore, the controller is configured to determine a crop row boundary consistency parameter associated with one or more crop rows of the plurality of crop row present within a region of interest of the captured image data. Moreover, the controller is configured to determine a quality metric for the guidance line based on the crop row boundary consistency parameter.