Warehouse Pallet Profiling Using 3D Vision and Point Clouds
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Solution Overview
Problem
Warehouses face inefficiencies and inaccuracies in storing and retrieving pallets due to unreliable supplier-provided information, leading to incorrect storage and potential damage during handling, which can result in liability issues and operational inefficiencies.
Innovation Solution
An automated pallet profiling system using stereoscopic, 3D, or 2D cameras, along with thermal imaging, to accurately identify pallet parameters such as dimensions, contents, quantity, damage, and lean, and attribute damage to the correct source, improving data accuracy and operational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated camera systems are deployed to profile pallets, then measurement precision and data accuracy improve, but device complexity and implementation cost increase
Solution Approach 1:
The camera system is designed to perform multiple functions: capturing images from multiple angles, detecting pallet dimensions, identifying damage, and tracking pallet movement through the warehouse. By consolidating these functions into a single integrated system, the patent reduces the need for multiple separate devices while maintaining high measurement precision across all parameters.
Solution Approach 2:
The patent introduces a computer vision processing system that acts as an intermediary between the camera hardware and the warehouse management decisions. This processing layer handles the complex tasks of image analysis, parameter extraction, and damage detection, allowing the physical camera system to remain relatively simple while achieving high measurement accuracy through sophisticated software algorithms.
2Reliability
If comprehensive pallet profiling is implemented, then reliability of warehouse operations improves, but loss of time during pallet processing increases
Solution Approach 1:
The system performs comprehensive pallet profiling at the point of entry into the warehouse, capturing all necessary information (dimensions, contents, damage, quantity) before the pallet enters the main storage and retrieval operations. This preliminary action ensures that all subsequent warehouse operations can proceed with reliable data without requiring additional profiling time at later stages.
Solution Approach 2:
The camera system operates continuously as pallets move through the profiling station, capturing images and data without interrupting the pallet flow. The system processes multiple pallets in sequence without idle time, maintaining continuous useful action while gathering comprehensive information for each pallet, thereby minimizing time loss while maximizing reliability.
3Measurement precision
If manual verification of supplier information is performed, then measurement precision improves, but productivity and operational efficiency deteriorate
Solution Approach 1:
The patent replaces manual verification processes with an automated computer vision system that uses cameras and image processing algorithms to capture and verify pallet information. This substitution eliminates the need for human operators to manually measure and record pallet parameters, thereby maintaining high measurement precision while dramatically improving productivity and operational efficiency.
Solution Approach 2:
The system enables pallets to be automatically profiled and verified as they pass through the camera station without requiring human intervention. The computer vision system independently performs all verification tasks, allowing the warehouse to process pallets at high speed while maintaining accurate information through automated self-verification rather than manual checking.
Data Source
AI summary
In one implementation, a system for automatically profiling pallets includes a frame defining an opening that is sized and shaped for a pallet to pass through, and cameras mounted to the frame, the cameras being configured to capture images of a pallet as it passes through the frame. The system further includes a profiling computer system that is configured to receive the images captured by the cameras and to automatically profile the pallet based, at least in part, on analysis of the images. Automatically profiling the pallet includes generating a point cloud representing the pallet based on the images, determining a size of the pallet based on the point cloud generated from images of the pallet, identifying contents of the pallet based on the images, and providing pallet information identifying, at least, the size and contents of the pallet to a warehouse management system in association with the pallet.