Computer Vision Package Sorting with Visual Feedback
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Solution Overview
Problem
Human error in sorting packages into correct containers during shipping can lead to delayed deliveries due to misreading labels or incorrect placement, despite some automation in package movement.
Innovation Solution
An overhead computer vision system with cameras and directional lights provides visual feedback to associates, illuminating regions with specific colors (green, red, or blue) based on the correct destination of packages, helping them identify and correctly place packages into containers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human associates manually sort packages into containers, then flexibility and adaptability are maintained, but sorting accuracy decreases due to misreading labels or incorrect placement
Solution Approach 1:
The system implements real-time visual feedback by displaying colored indicators (green for correct, red for incorrect) above containers. When a package is scanned and the system determines its correct destination, the appropriate container receives a green light signal, providing immediate feedback to the associate. This feedback mechanism resolves the contradiction by maintaining simple manual operations while significantly improving sorting accuracy through real-time guidance.
Solution Approach 2:
The patent introduces an intermediary system consisting of scanners, processors, and visual display devices that mediate between the package and the container. The scanner reads package labels, the processor determines correct destinations by comparing with shipping information, and the visual display intermediary guides the associate to the correct container. This intermediary layer improves reliability without requiring complete automation of the sorting process.
2Productivity
If automated systems are used for package movement, then productivity increases, but sorting accuracy may decrease due to automation errors or misreading labels
Solution Approach 1:
The system enables self-service by allowing the automated scanning and identification processes to occur without human intervention. Packages are automatically scanned as they move through the system, and the computer vision technology automatically identifies labels and determines correct destinations. This maintains high productivity while improving reliability by eliminating human reading errors.
Solution Approach 2:
The patent replaces manual mechanical reading processes with optical scanning and computer vision systems. Instead of human associates manually reading labels, automated scanners using optical technology capture and process label information. This substitution maintains productivity while improving accuracy by eliminating variations in human reading ability and fatigue-related errors.
3Reliability
If visual feedback systems are implemented to improve sorting accuracy, then reliability increases, but device complexity and cost increase
Solution Approach 1:
The system uses color changes as a simple yet effective visual feedback mechanism. Green lights indicate correct container destinations, while red lights indicate incorrect ones. This color-based feedback system provides intuitive guidance to associates without requiring complex interfaces or technology, improving reliability while keeping the system relatively simple and cost-effective.
Solution Approach 2:
The visual display devices serve as simple intermediaries that translate complex processing decisions into intuitive visual signals. Rather than requiring associates to interpret complex data or navigate complex systems, the intermediary display devices provide straightforward color-coded guidance. This keeps the user interface simple while maintaining high sorting accuracy through robust backend processing.
Data Source
AI summary
Embodiments herein describe a system for providing visual feedback to an associate when stowing packages into containers. As an associate carries a package towards a container, a camera disposed over the container captures an image of the package that a computer vision system uses to identify a barcode on the package. Using the barcode, the system can determine the desired destination of the package and whether the container the associate is approaching is the correct destination of the package. If so, the feedback system can activate a directional light on above the container which outputs a first color (e.g., green), thereby informing the associate that the container she is approaching is the correct container. However, if container is not the correct destination of the package, the directional light outputs a different color light (e.g., red) which informs the associate the container is the wrong destination for the package.