3D Map Building Using Radio Wave Signal Features
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Solution Overview
Problem
Existing methods for building 3D maps in large-scale environments, such as indoor spaces, face challenges in accurately reconstructing and merging 3D models due to variations in radio wave signal features, which affect navigation systems and localization accuracy.
Innovation Solution
A computer-implemented method and apparatus that obtain plural videos and video-related data units indicating radio wave signal features, reconstruct 3D models using techniques like Structure from Motion, and select and merge similar models based on beacon signal similarity to create a comprehensive 3D map, facilitating navigation and localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple 3D models are reconstructed from multiple videos to cover large-scale environments, then the coverage area increases, but the difficulty of accurately matching and merging models increases due to radio wave signal variations
Solution Approach 1:
The patent introduces video-related data units (radio wave signal features) as an intermediary to facilitate the matching of 3D models. Instead of directly comparing complex 3D model geometries, the system uses radio wave signal features received at different locations as a mediator to identify corresponding models, thereby improving matching precision across large-scale environments.
Solution Approach 2:
The patent transforms the matching problem from geometric parameter comparison to radio wave signal feature comparison. By changing the parameter basis from spatial coordinates to signal characteristics (RSSI values, signal strength), the system achieves more reliable model matching that is invariant to geometric transformations and more suitable for large-scale environment fusion.
2Measurement precision
If radio wave signal features are used to match 3D models, then the localization accuracy improves, but the complexity of data processing increases
Solution Approach 1:
The patent segments the complex matching problem into two independent stages: first extracting video-related data units (radio wave signal features) from videos, then using these segmented features for model matching. This segmentation simplifies the overall process by separating feature extraction from matching operations, making the system more manageable despite increased data processing requirements.
Solution Approach 2:
The patent creates video-related data units as simplified copies or representations of the actual radio wave signal environments. Instead of processing raw signal data directly, the system generates structured data units that capture essential signal features, reducing processing complexity while maintaining localization accuracy.
3Loss of information
If videos are taken at many locations to ensure complete environment coverage, then the completeness of 3D map increases, but the time required for data collection increases
Solution Approach 1:
The patent applies partial action by selecting and merging only those 3D models that have high similarity based on video-related data unit comparison. Instead of processing all collected videos equally, the system identifies and processes only the necessary subset of models required for complete coverage, reducing overall processing time while maintaining map completeness.
Data Source
AI summary
A computer-implemented method for building a 3D map, includes: obtaining plural videos and plural video-related data units, each of the plural video-related data units indicating a feature of radio wave signals received at a place where a corresponding video has been taken; reconstructing plural 3D models, respectively, based on the plural videos; selecting a pair of 3D models from the plural 3D models based on similarity between a corresponding pair of video-related data units; and merging the pair of 3D models to obtain the 3D map.