Optical Recognition for Pivot Center Guidance
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Solution Overview
Problem
Existing guidance systems for mobile machines, particularly in agriculture and construction, face challenges in accurately determining the center of center pivot irrigation systems on undulating terrain, leading to accuracy errors and inefficiencies in path determination, especially when the pivot does not form a perfect circle.
Innovation Solution
A path planning system that uses optical recognition on satellite or aerial imagery to identify characteristics such as pivot centers and boundaries, allowing for immediate determination of geographic locations and enabling automated guidance without the need for the operator to manually drive around the pivot to gather coordinates, even on complex terrains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine pivot center by manually driving around the pivot to gather coordinates, then the system can obtain pivot center location, but accuracy errors occur on undulating terrain and the process is time-consuming
Solution Approach 1:
The system performs preliminary action by obtaining satellite imagery before the field operation begins. The pivot center is identified from aerial or satellite images in advance, eliminating the need for time-consuming manual driving around the pivot during field operations. This preliminary identification of characteristics from imagery directly provides the pivot center coordinates needed for guidance.
Solution Approach 2:
The patent replaces the mechanical method of manually driving around the pivot to gather coordinates with an optical recognition system. Instead of using physical movement and mechanical coordinate collection, the system uses image processing and optical analysis of satellite or aerial imagery to automatically identify the pivot center, significantly reducing time and improving accuracy on undulating terrain.
2Measurement precision
If traditional manual methods are used to determine field characteristics, then the process is simple in concept, but accuracy deteriorates on undulating terrain where pivots do not form perfect circles
Solution Approach 1:
The patent replaces simple manual field surveying methods with an optical recognition system that analyzes satellite or aerial imagery. This substitution enables accurate identification of field characteristics including pivot centers, boundaries, and shapes regardless of terrain undulations. The system handles complex geometries by processing visual data from above, avoiding the limitations of ground-based manual methods.
Solution Approach 2:
The system transitions from two-dimensional ground-based manual measurement to three-dimensional aerial/satellite perspective. By viewing the field from above through imagery, the system can accurately identify pivot centers and boundaries even on undulating terrain where the pivot does not form a perfect circle when viewed from ground level. This dimensional change provides a comprehensive view that resolves terrain-related accuracy issues.
3Productivity
If optical recognition on satellite imagery is used to identify pivot centers directly, then accuracy and efficiency of path determination are enhanced, but the system requires access to and processing capability for satellite or aerial images
Solution Approach 1:
The system performs preliminary action by obtaining and processing satellite or aerial imagery before field operations begin. The optical recognition identifies field characteristics including pivot centers, boundaries, and shapes in advance, creating a digital representation that guides subsequent operations. This preliminary processing eliminates the need for time-consuming field surveys and enables immediate automated guidance setup.
Data Source
AI summary
In one embodiment, a method for automated guidance comprising receiving an image of a field; identifying one or more characteristics of the field in the image; determining one or more geographic locations corresponding to the one or more characteristics of the field in the image; determining a path to be followed in the field using the one or more geographic locations; and automatically guiding the machine to follow the path.