Shelf Imaging for Automated Product Label Mapping
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Solution Overview
Problem
Retail chains face challenges in automatically documenting product locations across stores due to variations in product packaging, orientation, and lighting conditions, making manual sorting of sale signage time-consuming and inaccurate.
Innovation Solution
A mobile base with an image capture assembly and control unit that captures images of product display units, extracts product-related data, and constructs a store profile indicating product locations, enabling automatic packaging of signage in the correct order.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sorting of signage is performed to match product locations, then signage can be correctly ordered for each store, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent replaces the manual mechanical sorting process with an automated optical imaging system. Image capture devices mounted on mobile robots automatically photograph product locations and labels throughout the store, eliminating the need for manual visual inspection and sorting of signage. The system uses computer vision algorithms to automatically extract product information from images and generate correctly ordered signage lists.
Solution Approach 2:
The system enables self-service automation where the imaging system independently captures images, processes product location data, and generates signage ordering information without human intervention. The mobile robots autonomously navigate store aisles, capture images at appropriate positions, and the control system automatically processes this data to produce the final signage sequence.
2Productivity
If automated image capture is used to document product locations, then data collection efficiency is improved, but variations in lighting, product orientation, and packaging make accurate identification difficult
Solution Approach 1:
The patent employs dynamic image capture strategies where the mobile imaging system adjusts its positioning and capture parameters based on real-time conditions. The system captures multiple images from different positions and angles, dynamically selecting and combining the best images for each product. This dynamic approach compensates for variations in lighting, product orientation, and packaging by gathering redundant data from multiple perspectives.
Solution Approach 2:
The system incorporates feedback mechanisms where captured images are immediately processed to assess quality and completeness. If images do not meet quality thresholds due to lighting or orientation issues, the system automatically triggers additional image capture passes. The feedback loop ensures that only sufficient-quality images are used for product identification, maintaining high accuracy despite environmental variations.
3Reliability
If multiple image capture devices are used to cover entire shelf units, then complete product documentation is achieved, but system complexity and cost increase
Solution Approach 1:
The patent divides the store into multiple segments or zones that are systematically captured by mobile imaging devices. Each shelf unit is segmented into captureable sections, and the system progresses through segments in an organized manner. This segmentation approach allows complete documentation of all products while using a manageable number of imaging devices that move through different segments sequentially rather than requiring all devices simultaneously.
Solution Approach 2:
The mobile imaging system is designed as a universal platform that can capture various types of product information (labels, barcodes, pricing, descriptions) and adapt to different store layouts and shelf configurations. The same imaging devices and processing algorithms handle diverse product types and display arrangements, reducing the need for specialized equipment for different capture scenarios and thereby limiting overall system complexity.
Data Source
AI summary
A store profile generation method includes moving a mobile base around a product facility which includes an arrangement of product display units for displaying products. Product labels are associated with the display units. The product labels display product-related data for the displayed products. With an image capture assembly mounted on the mobile base, images are acquired of the product display units at a sequence of locations of the mobile base. With a computer processor, the product-related data is extracted from the acquired images and a store profile is constructed, based on the extracted product-related data, a spatial characterization of the image capture assembly, and information on the locations of the mobile base when the images were acquired, which indicates locations of the product labels throughout the product facility.