3D Depth Imaging for Trailer Package Wall Density
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Solution Overview
Problem
Current methods for assessing trailer load efficiency fail to pinpoint inefficient packing areas within trailers, as they primarily measure fullness based on linear distance to package walls without breaking down the load into detailed package wall sections, thus missing air gaps and overall packing density.
Innovation Solution
A 3D depth imaging system that captures 3D image data of trailers, processes it using a load-efficiency app to analyze point cloud data, generate data slices, estimate missing data points, and calculate a load-efficiency score by dividing the trailer into regions, allowing for accurate detection of air gaps and wall density analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a three-dimensional camera combined with algorithms is used to detect trailer fullness in real-time, then the measurement of trailer fullness is improved, but the ability to pinpoint inefficient packing areas deteriorates
Solution Approach 1:
The patent divides the trailer interior into multiple regions (front, rear, left, right, center) and further segments each region into multiple package walls. This segmentation allows the system to not only measure overall fullness but also identify specific areas where packing efficiency varies, thereby pinpointing gaps and inefficient packing locations while maintaining real-time measurement capability.
Solution Approach 2:
The patent transitions from a single-dimensional fullness measurement to a multi-dimensional analysis by creating a three-dimensional model of the trailer interior with multiple package walls at different depths and positions. This dimensional expansion enables the system to detect not just overall fullness but also spatial distribution of packages, identifying gaps and packing inefficiencies in specific regions.
2Quantity of substance
If package wall density is calculated using traditional methods, then overall fullness is measured, but the identification of air gaps and packing inefficiencies deteriorates
Solution Approach 1:
The patent segments the package walls into multiple individual walls at different positions (front, rear, left, right, center) and calculates density for each wall separately. This segmentation enables the system to detect air gaps between adjacent walls and identify regions with lower packing density, thereby improving air gap detection while maintaining overall fullness measurement.
Solution Approach 2:
The patent applies local quality analysis by calculating package wall density independently for each region and each wall within a region. This allows the system to identify specific locations with poor packing quality (air gaps) while maintaining the overall fullness measurement, thereby improving measurement precision for detecting packing inefficiencies.
3Loss of information
If detailed package wall analysis is performed, then packing efficiency assessment is improved, but the complexity of the imaging and processing system deteriorates
Solution Approach 1:
The patent segments the complex task of analyzing package wall density into multiple simpler sub-tasks: capturing 3D images, processing images to identify package walls, dividing into regions, calculating density for each wall, and comparing against thresholds. This segmentation reduces the complexity of individual processing steps while achieving comprehensive packing efficiency assessment.
Solution Approach 2:
The system uses the 3D imaging data itself to automatically identify package walls, regions, and density variations without requiring manual intervention or complex external equipment. The processing algorithms work directly on the captured images to extract all necessary information, reducing the need for additional sensors or manual measurement tools.
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
This approach provides a detailed, accurate assessment of trailer load efficiency by analyzing package wall density, enabling informed decisions on improving packing efficiency and reducing waste space, leading to more efficient and profitable trailer operations.
Implementation Method 1
a three-dimensional (3D) depth camera configured to capture 3D image data
Data Source
AI summary
A method and apparatus for using a three-dimensional (3D) depth imaging system for use in commercial trailer loading is disclosed. The method and apparatus may be configured to determine a load-efficiency score for a trailer in a variety of ways. In one embodiment, the method and apparatus may determine the score by receiving a set of point cloud data based on 3D image data, analyzing the set of point cloud data, generating a set of data slices based on the set of point cloud data each data slice corresponding to a portion of the 3D image data, estimating a set of missing data points in each data slice in the set of data slices, and calculating a load-efficiency score based on the generated set of data slices and estimated set of missing data points.