Radar Crop Row Detection for Agricultural Vehicle Steering
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Solution Overview
Problem
Agricultural vehicles face challenges in accurately determining crop row properties, leading to cross-track errors and potential damage, as existing technologies like optical sensors are limited by canopy obstruction and environmental conditions.
Innovation Solution
The use of radar sensors to generate crop-radar-data, which is filtered to determine crop-property-data, enabling improved control of agricultural vehicles by providing vehicle-control-instructions for precise steering and speed adjustments, and allowing operation in various conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical sensors are used to detect crop rows, then the system can provide crop row location data, but the detection accuracy deteriorates due to canopy obstruction and environmental conditions
Solution Approach 1:
The patent replaces optical sensors with radar sensors to detect crop rows. Radar sensors use electromagnetic waves in the microwave frequency range, which can penetrate canopy obstructions and are not affected by darkness, fog, or other environmental conditions that limit optical sensor performance. This substitution resolves the contradiction by maintaining detection accuracy while eliminating sensitivity to harmful environmental factors.
2Measurement precision
If radar sensors are used to generate crop-radar-data, then the crop row detection accuracy improves, but the device complexity increases
Solution Approach 1:
The radar sensor system is designed to perform multiple functions: detecting crop row locations, determining crop row properties, and providing data for vehicle guidance and control. By using a single radar sensor type that can accomplish multiple detection tasks, the system reduces overall complexity compared to using multiple specialized sensors while maintaining high detection accuracy.
3Measurement precision
If filter-coefficient-values are applied to process crop-radar-data, then the determination of crop-property-data becomes more accurate, but the processing time increases
Solution Approach 1:
The system applies filter-coefficient-values to crop-radar-data in advance to generate filtered data that is then used to determine crop-property-data. By pre-processing the radar data with appropriate filters, the system improves the accuracy of subsequent property determination while managing processing time through efficient filter design and implementation.
4Manufacturing precision
If vehicle-control-instructions are provided for automatic steering control, then the cross-track error is reduced, but the system complexity increases
Solution Approach 1:
The system uses crop row detection data to generate vehicle-control-instructions that automatically adjust the vehicle's steering to maintain proper alignment with crop rows. The feedback loop continuously monitors crop row positions and adjusts steering accordingly, reducing cross-track error. This automated feedback control reduces the need for manual intervention and simplifies the overall control system despite the added automation capabilities.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution reduces cross-track errors and crop damage by providing more accurate crop row detection and vehicle control, even in challenging conditions like darkness, fog, or dense canopies, and allows for real-time adaptation of route plans.
Implementation Method 1
one or more radar-sensors configured to generate crop-radar-data representative of crop rows in the agricultural field
Data Source
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AI summary
An agricultural system is disclosed comprising one or more radar sensors configured to generate radar data representative of crop rows in an agricultural field. The system also comprises a controller configured to determine crop-property-data based on the radar data. The crop property data is representative of one or more properties of crop rows that are in a field.