Camera Calibration for Agricultural Implement Position Monitoring
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Solution Overview
Problem
Monitoring the health and function of tillage and planting implements while they are engaged with the ground is challenging due to visibility issues caused by soil and crop residue, limiting the effectiveness of sensors in autonomous agricultural operations.
Innovation Solution
A method involving camera calibration to detect the position of an implement relative to a tractor, capturing images using visible, UV, IR, thermal, or lidar representations, and generating a representation of the implement's position, including height, roll, pitch, drift, and lift, to enable real-time monitoring and adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are used to monitor implement health and function, then measurement capability is improved, but visibility is blocked by soil and crop residue
Solution Approach 1:
The patent uses visual targets mounted on the implement as intermediaries that can be detected by the camera system. These targets provide clear visual markers that can be seen through or around the obscuring soil and crop residue, allowing the system to indirectly monitor implement position and health without requiring direct line-of-sight to the implement components themselves.
Solution Approach 2:
The patent replaces direct mechanical/optical sensing of implement components with an image processing system that analyzes visual targets captured by a camera. This substitution allows monitoring through environmental obstacles by using computational image analysis rather than direct physical measurement, overcoming the visibility limitations imposed by soil and crop residue.
2Measurement precision
If operator monitors implement by looking to the rear, then implement health can be assessed, but operator safety is compromised and monitoring is not continuous
Solution Approach 1:
The system enables self-service monitoring by automatically capturing images of visual targets on the implement and processing these images to determine implement position and health parameters. This eliminates the need for operator intervention or direct observation, allowing continuous monitoring without compromising operator safety.
Solution Approach 2:
The patent implements a feedback system where images of visual targets are continuously captured and processed to provide real-time information about implement position and health. This automated feedback loop allows the operator to monitor implement conditions without directly observing the implement, improving both safety and continuity of monitoring.
3Measurement precision
If camera calibration is performed at multiple known positions, then detection accuracy is improved, but calibration time and complexity increase
Solution Approach 1:
The patent performs camera calibration in advance at multiple known positions before actual field operations. By completing this preliminary calibration work beforehand, the system establishes accurate detection parameters that can be used during field operations without requiring repeated calibration, thus improving detection accuracy while minimizing time loss during actual work.
Solution Approach 2:
The calibration process is performed periodically at predetermined intervals or before specific operations rather than continuously. This periodic calibration approach maintains detection accuracy over time while minimizing the total calibration time required, as the system only needs recalibration when conditions change or after a set period.
Data Source
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AI summary
A method includes calibrating a camera to detect a position of an implement relative to a tractor pulling the implement, traversing an agricultural field with the implement engaging soil of the field, capturing at least one image of the implement in the field by a camera carried by the tractor, and generating a first representation of a position of the implement relative to the field, using at least one computing device carried by the tractor. The calibration includes moving at least one of the tractor and the implement to each of a plurality of known positions, in series, relative to one another. At each of the known positions, at least one image of the implement is captured by the camera. Each of the known positions is correlated with the at least one image. The camera can alternatively be carried by the implement, and images of the tractor may be captured.