Warehouse Item Picking With AR Guidance and Virtual Layout
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Solution Overview
Problem
Current warehouse management systems are inefficient and prone to human error in locating and placing items, as they rely on manual navigation and lack an optimized overview of item distribution and picker tasks, leading to time consumption and increased costs.
Innovation Solution
A system utilizing a user tracking device with a processor and location markers, providing a 2D or 3D virtual representation of the warehouse, algorithms for spatial location, and augmented reality guidance to optimize item location and placement, along with a method for improving warehouse efficiency by classifying items based on priority and optimizing distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual navigation and traditional WMS addressing methods are used, then pickers can locate items using existing knowledge and diagrams, but the process is time-consuming and requires multiple manual tasks including locating position, identifying rack location, finding the path, and determining shelf location
Solution Approach 1:
The patent introduces a mobile computing device as an intermediary between the picker and the warehouse environment. This device captures images of the warehouse, automatically identifies the picker's location using image recognition algorithms, and provides guided navigation to items. This eliminates the need for manual position tracking and diagram interpretation, directly reducing location time while maintaining high productivity
Solution Approach 2:
The patent replaces manual mechanical navigation methods with automated optical and computational systems. Instead of manually interpreting diagrams and counting rows/racks, the system uses camera-based image capture and automated image recognition algorithms to identify location and provide navigation guidance, significantly reducing the time required while maintaining accurate item location
2Ease of operation
If traditional spreadsheet-based task management is used, then tasks can be listed with item locations, but there is no overview of item distribution optimization or picker task optimization
Solution Approach 1:
The patent creates a multi-functional system that simultaneously provides simple task listing capabilities (like traditional spreadsheets) and advanced analytical features. The mobile computing device not only displays task information but also captures warehouse images, analyzes item distribution patterns, optimizes picker routes, and provides real-time navigation guidance, eliminating the need for separate optimization tools while maintaining operational simplicity
Solution Approach 2:
The system implements continuous feedback loops where warehouse images are captured and analyzed to provide real-time information about item locations and distribution. This feedback enables dynamic optimization of picker tasks and routes based on actual warehouse conditions, while the mobile interface presents this complex information in an easily digestible format that maintains operational simplicity
3Measurement precision
If automated image recognition and virtual representation systems are implemented, then user location and item location can be accurately determined and displayed, but the device complexity and system requirements increase
Solution Approach 1:
The system employs self-service mechanisms where the mobile computing device automatically captures warehouse images, independently processes them through image recognition algorithms to identify the picker's location, and autonomously generates navigation guidance. This self-contained approach achieves high location accuracy without requiring complex external infrastructure, as the device performs all functions locally
Solution Approach 2:
The patent transforms the complex problem of precise location tracking by changing the fundamental parameter from coordinate-based navigation to image-based recognition. Instead of requiring the system to process and interpret complex spatial coordinates and rack addresses, the system uses visual pattern recognition to directly identify locations from images, simplifying the overall system architecture while maintaining high precision
4Reliability
If no optimization system is used, then item placement relies on manual processes subject to human error, but implementing optimization requires sophisticated algorithms and processing
Solution Approach 1:
The patent creates a virtual representation (digital twin) of the warehouse that mirrors the physical environment. This virtual copy is generated from captured images and used to plan and optimize item placement before executing in the physical warehouse. This copying approach enables sophisticated optimization algorithms to operate on the virtual model, ensuring placement accuracy while managing automation complexity through simulation
Data Source
AI summary
In a system and method for placing and picking items in a warehouse. the correct location of the item is displayed on a virtual depiction of the warehouse. the person tasked with placing or picking an item is visually guided to the item in question. and the placement of items and movement of persons and goods is optimized for the warehouse.