Exception Detection in Automated Optical Code Reading via 3D Models
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Solution Overview
Problem
Automated optical code readers face challenges in accurately identifying and handling errors and unexpected events, such as 'no code', 'multiple codes', 'no object', and 'multiple objects' exceptions, which can lead to incorrect data processing and transaction errors.
Innovation Solution
The system employs an automated imager-based optical code reading system with a conveyor system, object measurement system, optical code reading system, and exception handling system to generate three-dimensional models of objects and determine the intersection of back projection rays with these models, allowing for real-time identification and handling of exceptions through a processor and associated software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated optical code reading systems are used to improve productivity, then reading speed and throughput increase, but error identification and handling complexity increases
Solution Approach 1:
The system segments error handling into distinct exception types (no code, multiple codes, no object, multiple objects) with specific detection rules for each type. This segmentation allows the system to manage complexity by treating different error conditions as separate, manageable units rather than a monolithic error handling problem.
Solution Approach 2:
The system performs preliminary actions by generating three-dimensional models of objects and calculating back projection rays before attempting code reading. This preliminary geometric modeling enables the system to predict and identify potential exceptions before they occur, allowing proactive error handling rather than reactive processing.
2Reliability
If exception handling systems are added to improve reliability, then error identification accuracy increases, but device complexity increases
Solution Approach 1:
The system implements feedback mechanisms where the exception handling system continuously monitors code reading attempts, compares actual results with expected outcomes based on three-dimensional models, and adjusts processing accordingly. This feedback loop improves reliability by ensuring errors are detected and corrected, while the automated nature of the feedback reduces the perceived complexity.
Solution Approach 2:
The patent introduces an intermediary exception handling system that acts as a mediator between the optical code reading system and the data processing system. This intermediary layer absorbs and manages error handling complexity, providing a clean interface to the rest of the system while improving overall reliability through systematic error management.
3Productivity
If manual intervention is reduced to improve productivity, then automation increases, but difficulty of detecting and measuring exceptions increases
Solution Approach 1:
The system implements self-service capabilities where the automated optical code reading system autonomously detects, classifies, and handles exceptions without human intervention. The system uses pre-defined rules and three-dimensional model comparisons to automatically identify error types and implement appropriate corrective actions, maintaining high productivity while managing exception detection complexity through automation.
Solution Approach 2:
The patent replaces manual mechanical inspection and error detection with automated optical sensing and computational analysis. By substituting human operators with automated image capture devices, processors, and algorithms that analyze back projection ray intersections with three-dimensional models, the system increases automation while making exception detection more consistent and measurable through digital rather than manual processes.
Data Source
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AI summary
An automated system for reading optical codes includes a conveyor system to automatically transport objects and an object measurement system positioned along the conveyor system to measure the transported objects. In one configuration, the object measurement system generates model data representing three-dimensional models of the objects; multiple image capture devices positioned along the conveyor system capture images as the objects are transported to enable an optical code reading system to read optical codes that are captured in the images. An exception identification system associates optical codes with the three-dimensional models to determine whether an exception has occurred.