Indoor Route Mapping Using AR Grid and Visual Tracking
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Solution Overview
Problem
Existing technologies for indoor location tracking are either inaccurate or costly, making it difficult to efficiently navigate and route within indoor environments, such as retail stores.
Innovation Solution
A system utilizing Augmented Reality (AR) for indoor route mapping, where a user's device streams video to create a grid-based data structure of the indoor location, allowing for accurate identification and association of items or objects with corresponding grid cells, and generating efficient routes to these items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If Bluetooth beacons are used for indoor location tracking, then the system cost is reduced, but the location accuracy is insufficient for practical use
Solution Approach 1:
The patent uses visual copies (images) of the physical environment captured by a smartphone camera to create a digital map. Instead of relying on expensive Bluetooth beacons or complex camera systems, the system creates a simplified grid representation of the store layout from ordinary visual data, achieving both low cost and high accuracy.
Solution Approach 2:
The patent replaces the mechanical/electromagnetic positioning systems (Bluetooth beacons, overhead cameras) with a computational approach that processes visual images to determine location. The system uses image recognition and grid mapping algorithms to substitute for traditional hardware-based positioning infrastructure.
2Measurement precision
If overhead cameras and lighting systems are deployed for indoor tracking, then location accuracy is improved, but the hardware and software resource investment is substantial
Solution Approach 1:
The patent extracts the essential function of location tracking from complex overhead camera systems and implements it using a simple smartphone camera. By taking only the necessary visual data from the user's perspective and processing it locally, the system eliminates the need for expensive infrastructure while maintaining accuracy.
Solution Approach 2:
The system uses the user's own smartphone to perform both the mapping and tracking functions. The user's device captures images, processes them to create the grid map, and tracks their location within that map - making the system self-sufficient without requiring external hardware infrastructure.
3Measurement precision
If a comprehensive indoor mapping system is implemented, then routing accuracy is improved, but the time required to establish the mapping is significant
Solution Approach 1:
The patent performs preliminary actions by capturing multiple images at different locations and orientations before the actual routing task. These pre-captured images are used to build the grid map in advance, so that when routing is needed, the system can quickly reference the pre-established mapping without requiring real-time comprehensive scanning.
Solution Approach 2:
The system captures more images than strictly necessary to cover the entire store area, creating a redundant set of visual data that can be processed into the grid map. This excessive sampling ensures comprehensive coverage and high accuracy while the processing can be done in batches, reducing the perceived time requirement.
Data Source
AI summary
An indoor location is mapped into a grid comprising grid cells, each cell associated with items or objects detected as being present in the corresponding cell. The grid, grid cells, and linked items and/or objects are generated and updated using an Augmented Reality (AR) algorithm that maps a physical environment into cells and measures distances and directions within the environment relative to each cell. Walking paths (routes) to the items within the indoor location are generated using the grid information. As a user walks a path, the user's position within the indoor location is mapped and tracked to the cells and the path revised based on the user's actual position. A user device provides video via an AR application to track the user's position; a rendering of the position and path are superimposed within the video being viewed by the user on the user-operated device.