Work Machine Surface Scanning for Real-Time Fill Estimation
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Solution Overview
Problem
Current methods for estimating the amount of fill material needed for construction projects are inaccurate and lack real-time data, leading to inefficiencies in determining the remaining number of truckloads required to complete earthwork, as they do not provide dynamic updates on bank cubic yardage, swell factor, and compaction factors.
Innovation Solution
A system and method utilizing real-time surface scanning with equipment like stereo cameras, radar, and LiDAR mounted on work machines to dynamically estimate surface characteristics, such as bank yardage, swell factor, and compaction factor, enabling immediate comparison and prediction of material needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional estimation methods are used to determine fill material requirements, then the process is simple and quick, but the accuracy of material quantity predictions is poor
Solution Approach 1:
The patent replaces traditional manual estimation methods with an automated optical measurement system using stereo cameras and image processing algorithms. The system captures images of the work area, generates three-dimensional surface models, and automatically calculates bank cubic yardage, swell factors, and compaction factors through digital image analysis, eliminating the need for physical surveying equipment and manual calculations.
Solution Approach 2:
The patent creates a digital copy of the physical work area by generating three-dimensional surface models from stereo camera images. These digital models serve as virtual representations that can be analyzed, stored, and compared over time to track material movement and compaction, providing accurate measurements without physically disturbing the site.
2Productivity
If traditional estimation methods are used, then the system is simple to operate, but real-time dynamic updates on material needs are not provided
Solution Approach 1:
The patent implements continuous surface scanning by mounting stereo cameras on moving work machines, allowing the system to continuously capture and process surface data as the machine traverses the work area. This enables real-time generation of three-dimensional models and continuous updating of material requirement estimates without interrupting work operations.
Solution Approach 2:
The system performs self-calibration and automatic data processing by using the motion of the work machine itself to navigate and scan the work area. The stereo camera system automatically captures images, processes them through algorithms to generate three-dimensional models, and calculates material parameters without requiring external surveying equipment or manual intervention.
3Measurement precision
If multiple surveys are performed before and after material movement to estimate compaction factors, then more accurate compaction data is obtained, but significant time is lost in performing sequential surveys
Solution Approach 1:
The patent performs preliminary surface scanning and three-dimensional model generation before material is moved or compacted. By capturing the initial surface state and storing it as a digital reference, the system can later compare against post-compaction images to calculate compaction factors, eliminating the need to wait for physical re-surveying after each compaction pass.
Solution Approach 2:
The system implements continuous feedback by comparing real-time surface scans against the initial three-dimensional model, automatically calculating changes in surface elevation and volume. This provides ongoing updates on compaction progress and material requirements, allowing operators to make immediate adjustments without waiting for sequential survey results.
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
Enables real-time estimation of material requirements, improving the accuracy of predicting the number of truckloads needed and optimizing the earthwork process by providing immediate and dynamic updates on material needs.
Implementation Method 1
a first image data source onboard the work machine and configured to capture a first image of a surface
Implementation Method 2
radar, and LiDAR
Implementation Method 3
radar sensor...configured to capture radar data corresponding to a traversed portion of the work area
Implementation Method 4
stereo cameras, radar, and LiDAR
Implementation Method 5
LiDAR
Data Source
AI summary
System and methods are provided for dynamic characterization of an area to be worked using a work implement of a work machine. First real-time data (e.g., surface scan data) are collected in a forward direction via a first sensor external to or onboard the work machine, and second real-time data (e.g., surface scan data) are collected for at least a traversed portion of the work area via a second onboard sensor. Characteristic values of a ground material in the work area are determined based on at least the first and second data corresponding to a given surface, and outputs are generated corresponding to at least a determined amount of material needed to achieve target values for the work area, based on at least one of the characteristic values. Certain characteristic values based on the real-time data may be used to estimate, among other things, how many truck loads are still required for the work area.