Map Database Creation for Visual SLAM Lighting Adaptation
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Solution Overview
Problem
Current visual SLAM-based indoor positioning systems are affected by changes in lighting conditions, leading to reduced accuracy and robustness, as they rely on maps created under specific lighting conditions that do not account for variations in time, weather, and lamp lighting, resulting in positioning failures when used in different lighting scenarios.
Innovation Solution
A map database creation method that divides the database into levels based on factors like time, weather, and lamp lighting, creating sub-databases for each combination of factors, allowing for the selection of an initial map matching current lighting conditions and continuously expanding the database with new maps to ensure accurate positioning across varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single map is created for visual SLAM positioning, then the mapping process is simple and fast, but the positioning accuracy deteriorates when lighting conditions change
Solution Approach 1:
The patent divides the single map into multiple sub-maps organized in a hierarchical database structure. Each sub-map corresponds to specific lighting conditions (e.g., morning, afternoon, evening, night) and weather conditions. This segmentation allows the system to select the appropriate sub-map for current conditions, maintaining positioning accuracy while preserving the efficiency of individual map creations.
Solution Approach 2:
The patent introduces lighting condition parameters and weather parameters as key attributes for organizing maps. By changing these parameters into discrete categories (time of day, weather conditions), the system can efficiently select and switch between appropriate maps without requiring complete remapping, thus maintaining accuracy without significant productivity loss.
2Ease of manufacture
If a map is created under specific lighting conditions, then the mapping process is straightforward, but the positioning reliability decreases when used in different lighting conditions
Solution Approach 1:
The patent performs preliminary actions by creating multiple maps in advance under different lighting and weather conditions during system development. These pre-created maps are stored in the database with their corresponding condition metadata. When actual positioning is needed, the system simply selects the pre-prepared map that matches current conditions, avoiding the need to create maps on-demand for each condition.
Solution Approach 2:
The system incorporates feedback mechanisms where the detected lighting conditions and weather parameters are used to select the most appropriate map for positioning. This feedback loop ensures that the system continuously adapts to current environmental conditions by selecting maps that match the actual conditions, thereby maintaining high reliability.
3Measurement precision
If the map database includes multiple maps for different lighting conditions, then the positioning accuracy improves, but the device complexity increases
Solution Approach 1:
The patent adds new dimensions to the traditional 2D map structure by incorporating lighting condition dimensions and weather condition dimensions. The database is organized as a hierarchical structure with levels representing different conditions (e.g., time-based levels, weather-based levels). This dimensional expansion allows efficient organization and retrieval of condition-specific maps without creating a completely flat complex structure.
Solution Approach 2:
The patent implements a nested database structure where maps are organized within hierarchical levels. The database contains root nodes that branch into different condition categories, which in turn contain specific maps. This nesting approach allows the system to manage multiple maps in an organized, scalable manner, reducing the practical complexity of storing and retrieving condition-specific maps.
4Device complexity
If the system uses a single map for positioning, then the system complexity is low, but the adaptability to different lighting and weather conditions is poor
Solution Approach 1:
The patent introduces dynamic selection capabilities where the system automatically adapts to current lighting and weather conditions by selecting the most appropriate map from the database. The system monitors environmental parameters (lighting, weather) and dynamically switches between maps accordingly. This dynamic behavior provides high adaptability while keeping the base system structure relatively simple.
Solution Approach 2:
The patent creates a universal positioning system that can handle multiple lighting conditions and weather scenarios through a single integrated database structure. The same database framework supports all condition variations, making the system multi-functional without requiring separate systems for each condition. This universality maintains manageable complexity while achieving high adaptability.
Data Source
AI summary
A map database creation method is provided. The method includes: obtaining a factor set including factors; dividing a map database into levels based on the factors, and taking each interval of the last level as one sub-database; creating an initial map based on a factor value of each factor corresponding to each sub-database, and creating the sub-database as an initial map database by storing the corresponding initial map in the sub-database; finding the initial map matching a current lighting condition from the initial map database based on the current lighting condition, and taking the found initial map as a positioning map; and performing a visual positioning based on the positioning map, creating an expanded map corresponding to the current lighting condition based on the visual positioning, and creating the sub-database corresponding to the current lighting condition as an expanded map database by storing the corresponding expanded map in the sub-database.