Augmented Reality Loading Guidance for Storage Optimization
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Solution Overview
Problem
Loading items efficiently in unarranged or unknown sequences is challenging due to the lack of real-time data on item sizes, weights, and locations, leading to suboptimal space utilization and increased training costs for workers.
Innovation Solution
An augmented reality system that generates a three-dimensional map of the storage area based on existing packages, determines the optimal location for new items using their dimensions, weights, and placement rules, and provides a virtual overlay to workers via transparent displays, guiding them on the correct placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workers manually load items without real-time guidance, then device complexity is reduced, but loading efficiency and space utilization deteriorate
Solution Approach 1:
The patent creates a virtual copy of the physical storage space by generating a three-dimensional digital twin model. This virtual model replicates the storage area's geometry, existing items, and spatial relationships, allowing the system to simulate and determine optimal placement locations without physically manipulating each item. The digital twin serves as a virtual workspace that enables real-time calculations and visualizations for loading optimization.
Solution Approach 2:
The patent replaces manual mechanical decision-making with an automated computational system. Instead of workers physically trying different item placements to determine optimal arrangements, the system uses algorithms to calculate optimal positions based on item dimensions, weights, and storage constraints. The mechanical process of trial-and-error loading is substituted with digital simulation and computational optimization.
Solution Approach 3:
The patent introduces an intermediary system between the worker and the loading task. This intermediary consists of the three-dimensional map visualization and augmented reality interface that displays optimal placement locations overlaid on the physical storage space. The intermediary translates complex optimization calculations into intuitive visual guidance, mediating between the worker's actions and the optimal loading strategy without requiring the worker to perform complex calculations themselves.
2Manufacturing precision
If workers are trained extensively to load items efficiently, then loading quality improves, but training time and costs increase
Solution Approach 1:
The patent implements real-time feedback mechanisms that provide immediate guidance to workers during the loading process. The three-dimensional map and augmented reality interface continuously update to show optimal placement locations based on current storage conditions and incoming items. This feedback loop eliminates the need for extensive prior training by providing on-demand guidance that adapts to changing circumstances, allowing workers to achieve high loading quality through real-time information rather than memorized procedures.
Solution Approach 2:
The patent performs preliminary calculations and visualizations before the actual loading occurs. The system pre-determines optimal placement locations by analyzing item characteristics and storage constraints in advance, then presents these pre-planned arrangements to workers through the three-dimensional map interface. This preliminary action shifts the cognitive workload from during-loading decision-making to pre-loading planning, reducing the need for workers to learn complex loading strategies in real-time.
3Productivity
If real-time tracking and three-dimensional mapping are implemented, then loading optimization improves, but computational requirements and system complexity increase
Solution Approach 1:
The patent segments the storage space into discrete, manageable units or zones within the three-dimensional map. Instead of treating the entire storage area as a single complex space, the system divides it into smaller regions that can be independently managed and visualized. This segmentation reduces the computational complexity of tracking and mapping by breaking down the overall problem into smaller, more manageable sub-problems, allowing real-time updates without excessive computational energy consumption.
Data Source
AI summary
Systems, methods, and computer-readable storage media for using augmented reality to improve loading, and in particular improve loading when the types and order of items to be loaded is unknown. A server uses information regarding the packages which have already been stored in a storage area to generate a virtual map of where the stored packages currently are placed. Upon receiving information indicating a subsequent package is going to be stored, the server can identify the best place to store that package in the storage area, then communicate that storage location to a device used by a worker. The worker can then have a visual indication showing where and how to place the subsequent package.