3D Box Dimensioning With Integrated Barcode and Depth Sensing
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Solution Overview
Problem
Conventional box dimensioning systems are inefficient due to costly setups, lack of integration with barcode scanning, and complexity in handling irregularly shaped objects, hindering widespread adoption and increasing costs.
Innovation Solution
A system integrating 2D imaging and 3D dimensioning capabilities using a scanner with image capturing devices, sensors, and processors to determine pixel coordinates, corner points, and dimensions, seamlessly incorporating barcode decoding and depth estimation for accurate dimension calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional dimensioning systems (LIDAR, TOF) are used, then depth measurement capability is achieved, but device complexity and cost increase
Solution Approach 1:
The patent combines 2D image capture and 3D depth measurement into a single integrated scanner device. The image capturing device and depth sensing components are merged into one unit, eliminating the need for separate LIDAR or TOF systems. This integration maintains depth measurement precision while reducing overall system complexity and cost.
Solution Approach 2:
The scanner is designed to perform multiple functions: 2D image capture, 3D depth measurement, and barcode scanning, all within a single device. This multi-functionality replaces the need for specialized laser units and rotating stands, simplifying the system while maintaining measurement capabilities.
2Adaptability or versatility
If separate systems are used for barcode scanning and dimensioning, then specialized functionality is achieved, but device complexity and cost increase
Solution Approach 1:
The patent integrates barcode scanning capability directly into the dimensioning system. The image capturing device captures both the object for dimensioning and any barcodes on the object simultaneously, eliminating the need for separate barcode scanning systems and reducing overall complexity.
Solution Approach 2:
The scanner performs multiple functions including dimensioning, barcode scanning, and label reading within a single device. This universal design allows the system to handle various logistics tasks without requiring multiple specialized systems, reducing both complexity and cost.
3Adaptability or versatility
If conventional methods handle irregularly shaped objects, then dimensioning capability is achieved, but setup cost and complexity increase
Solution Approach 1:
The patent replaces mechanical dimensioning methods (such as physical measuring tools and rotating stands) with optical and computational approaches. The image capturing device and depth sensing work together with image processing algorithms to automatically determine dimensions of irregularly shaped objects without requiring specialized mechanical setups, reducing both cost and complexity.
Solution Approach 2:
The system uses depth information and pixel coordinates to dynamically calculate dimensions based on the object's actual shape. By changing from fixed mechanical measurement parameters to flexible computational parameters, the system can adapt to irregular shapes without requiring specialized setups for each object type.
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 efficient and cost-effective box dimensioning with integrated barcode scanning, capable of handling both regular and irregular shapes, providing comprehensive object volume, dimension, and barcode value information.
Implementation Method 1
The scanner is configured to capture one or more images of at least one object with at least one image capturing device
Implementation Method 2
one or more sensors operationally coupled with the at least one image capturing device. The one or more sensors are configured to determine a depth information and a distance information of each pixel
Data Source
AI summary
A system and method for box dimensioning are disclosed. The system comprises a scanner to capture images of at least one object with at least one image capturing device and create one or more coloured map images for obtaining pixel information. Further, one or more sensors are configured to determine depth and distance information of each pixel of one or more coloured map images. Further, the system comprises at least one system processor to determine a plurality of pixel coordinates of each corner of a plurality of corners of at least one object based at least on distance information, determine a plurality of corner points of each corner based at least on plurality of pixel coordinates, map each corner point of plurality of corner points to a respective predefined distance, and determine a plurality of dimensions of at least one object based at least on mapping and determined depth information.