Aerial Image Positioning for Single-Pass Field Rock Removal
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Solution Overview
Problem
Existing methods for removing rocks from agricultural fields are inefficient, often requiring manual operation and multiple passes, which are labor-intensive and costly, and pose safety hazards.
Innovation Solution
An image-collection vehicle captures images of a target geographical area, using avionic telemetry information to determine object locations, and an object-collection system is guided to pick up identified objects based on these locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual implements (rakes, windrowers, sieves) are used to clear fields of rocks, then some rocks can be removed, but the failure rate is high and multiple passes are required, resulting in labor-intensive operations and high costs
Solution Approach 1:
The system performs preliminary detection of rock locations using aerial imaging and GPS technology before the rock removal operation. This allows the collection vehicle to navigate directly to identified rocks in a single pass, eliminating the need for multiple passes and manual searching, thereby dramatically improving productivity and reducing time loss
Solution Approach 2:
The system creates a digital map copy of the field with precise rock locations marked using aerial photography and GPS coordinates. This digital representation allows the collection vehicle to follow an optimized path without needing to physically search for rocks, reducing operational time and increases productivity
2Productivity
If manual operation and human intervention are used to pick rocks, then rocks can be removed, but labor costs increase and the work is slow and unpleasant
Solution Approach 1:
The system enables the rock collection vehicle to operate autonomously using automated navigation based on GPS coordinates of rocks identified by the aerial imaging system. The vehicle self-navigates to each rock location and performs collection without human intervention, eliminating manual labor while maintaining high removal speed
Solution Approach 2:
The system replaces manual mechanical rock picking with an automated guided vehicle system that uses GPS navigation and automated control. This substitution eliminates the need for human operators to perform slow, unpleasant manual picking while maintaining efficient rock removal speeds
3Productivity
If automated agricultural equipment operates in fields with rocks, then field operations can proceed, but rocks foul up equipment and create safety hazards, resulting in expensive repairs and lost productivity
Solution Approach 1:
The system performs preliminary identification and mapping of all rocks in the field before automated agricultural equipment arrives. Rocks are marked with GPS coordinates and presented to the operator, allowing proactive removal or avoidance of rocks that could damage equipment, thereby ensuring continuous productive operation and equipment safety
Solution Approach 2:
The system takes preliminary action to neutralize the harmful effect of rocks by identifying and removing them before they can cause damage to automated agricultural equipment. This prevents the harmful interaction between rocks and equipment, ensuring both safety and operational continuity
Data Source
AI summary
An object identification method is disclosed. The method includes obtaining images of a target geographical area and telemetry information of an image-collection vehicle at a time of capture, analyzing each image to identify objects, and determining a position of the objects. The method further includes determining an image capture height, determining a position of the image using the capture height and the telemetry information, performing a transform on the image based on the capture height and the telemetry information, identifying the objects in the transformed image, determining first pixel locations of the objects within the transformed image, performing a reverse transform on the first pixel locations to determine second pixel locations in the image, and determining positions of the objects within the area based on the second pixel locations within the captured image and the determined image position.