Indoor Positioning via Head-Mounted Display and Shared Maps
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Solution Overview
Problem
Indoor positioning systems face challenges in achieving accurate and consistent location tracking due to the inability to receive GPS signals indoors and the complexity and cost of using hardware beacons like Bluetooth, RFID, and Zigbee, which are affected by environmental changes.
Innovation Solution
An indoor space positioning method using a head-mounted display with a camera and processor that captures initial images, downloads share maps from a server, and applies SLAM algorithms to track location, enabling precise positioning by dividing indoor space into blocks and updating maps dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS technology is used for positioning, then positioning accuracy is improved, but it cannot be applied indoors
Solution Approach 1:
The patent creates a virtual map copy of the indoor environment that can be stored and processed locally in head-mounted displays. This copy enables positioning functionality similar to GPS but adapted for indoor use by representing spatial relationships in a digital format that can be manipulated without external satellite signals.
Solution Approach 2:
The patent introduces shared maps as an intermediary between users and the indoor environment. These maps serve as a common reference framework that multiple users can access simultaneously, enabling consistent positioning and navigation across different devices without requiring direct environmental scanning by each user.
2Adaptability or versatility
If hardware beacons (Bluetooth, RFID, Zigbee) are deployed for indoor positioning, then indoor positioning capability is achieved, but system complexity and cost increase
Solution Approach 1:
The patent extracts the positioning functionality from complex hardware beacon systems and implements it using standard mobile device components (cameras, processors, communication interfaces). By removing the need for specialized beacon hardware, the system achieves indoor positioning capability while significantly reducing system complexity.
Solution Approach 2:
The patent makes standard mobile device components perform multiple functions - the camera captures images for both environmental recognition and positioning, the processor handles both general computation and SLAM algorithms, and the communication interface enables both data transmission and map sharing. This multi-functionality eliminates the need for dedicated positioning hardware.
3Adaptability or versatility
If environmental characteristics are scanned to create anchors, then positioning can be established, but identification accuracy decreases due to environmental changes
Solution Approach 1:
The patent performs preliminary scanning and map creation actions during periods when environmental changes are minimal or well-documented. The shared maps are established in advance and stored on the server, allowing users to benefit from pre-processed positioning data without experiencing the accuracy degradation that would result from real-time environmental variability.
Solution Approach 2:
The system implements feedback mechanisms where positioning accuracy is continuously monitored and used to adjust the scanning and map updating processes. When environmental changes are detected, the system can trigger re-scanning or map updates to maintain identification accuracy, creating a closed-loop system that adapts to environmental variability.
4Measurement precision
If complete maps of indoor spaces are downloaded, then positioning accuracy is improved, but data transmission time and energy consumption increase
Solution Approach 1:
The patent divides the complete indoor map into segmented shared maps that are distributed across multiple servers or storage locations. Users can download only the specific segments relevant to their current location and navigation needs, rather than transferring entire map datasets. This segmentation reduces transmission time while maintaining positioning accuracy through selective data retrieval.
Data Source
AI summary
An indoor space positioning method includes capturing an initial image using the camera in a head-mounted display (HMD) and enabling the transmission interface to download from a server the initial share map that corresponds to the initial image. The processor in the head-mounted display locates the head-mounted display at an initial location in an indoor space.