Overhead Image Selection for Worksite Machine Control
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Solution Overview
Problem
Existing systems face challenges in determining the performance quality of overhead images from various sources, leading to increased costs and computational complexity in planning and controlling work machines, as they often rely on images from private providers or manually testing multiple images, which is time-consuming and inefficient.
Innovation Solution
An automated system and method that analyzes overhead images to determine their performance quality and selects the most suitable images for worksite operation planning and machine control, utilizing image selection systems to streamline the process and reduce costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If images from private providers are used, then image quality may be improved, but costs increase
Solution Approach 1:
The system uses free or low-cost public overhead images (such as satellite imagery) as a substitute for expensive private provider images. By implementing automated quality assessment, the system ensures that these cheaper images meet the required quality standards for worksite operation planning and machine control, thereby reducing costs while maintaining image quality.
2Measurement precision
If multiple images are manually tested, then image quality can be ensured, but time consumption increases
Solution Approach 1:
The system replaces manual image testing with an automated image quality assessment system that uses computational algorithms to evaluate image quality metrics. This automated approach rapidly processes and ranks multiple overhead images based on their suitability for worksite operations, eliminating the time-consuming manual testing process while ensuring consistent quality evaluation.
3Productivity
If automated image selection is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system introduces an intermediary image quality assessment module that acts as a bridge between raw overhead images and the worksite operation planning system. This intermediary automatically evaluates image quality, ranks candidates, and selects the most suitable images, thereby improving productivity through automation while managing complexity by creating a dedicated, modular assessment layer.
Data Source
AI summary
A computer implemented method includes obtaining, from one or more image providers, a set of one or more overhead images of a worksite, each overhead image including values indicative of a characteristic at different geographic locations across the worksite; identifying an image performance quality metric for each overhead image based on an image performance quality model; determining if at least one overhead image can be selected, as a selected image, based on the identified image performance quality metrics for the one or more overhead images; selecting, in response to determining that at least one overhead image can be selected, as a selected image, the at least one overhead image and outputting the at least one selected image for use in control of the mobile work machine and generating control signals to control the mobile work machine based, at least, on the at least one selected image.