Self-Localizing Anchor Devices for Indoor Positioning
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Solution Overview
Problem
Current indoor localization systems for tracking personnel in emergency situations, such as building fires, are hindered by the need for costly and time-consuming installation of statically placed anchor devices, which limits their deployment and effectiveness due to the requirement for precise placement and maintenance, and are often rendered inoperable by power outages.
Innovation Solution
The development of self-localizing anchor devices that can be dynamically deployed and transition between operating states, allowing them to determine their position and serve as reference points for tags within a scene, reducing the need for static installation and enabling rapid setup of accurate indoor positioning systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statically mounted anchor devices are precisely placed to enable accurate localization, then measurement precision is improved, but device complexity and installation time increase
Solution Approach 1:
Anchor devices perform self-localization by determining their positions autonomously through wireless communication with other anchor devices, eliminating the need for manual precise placement and reducing installation complexity while maintaining localization accuracy
Solution Approach 2:
The system transitions from static anchor device placement to dynamic self-localization where anchor devices can be freely deployed and automatically determine their positions, making the system adaptable to different environments without reinstallation
2Measurement precision
If multiple candidate positions are calculated using different techniques, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system calculates errors for each candidate position and uses this feedback to select the most accurate position, improving measurement precision through error-aware selection while managing computation time by evaluating multiple candidates efficiently
3Measurement precision
If error estimation is performed for multiple candidate positions, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system changes the parameter of position accuracy by estimating errors for multiple candidate positions and selecting the best one, improving measurement precision while managing energy consumption through selective error estimation rather than continuous high-precision calculations
Data Source
AI summary
Examples of systems and methods described herein may be used to track a tagged object through a scene. Techniques are described herein to calculate a position of the tag using wireless communication with multiple anchor devices. In some examples, the anchor devices may be self-localizing, e.g., they may dynamically determine their position and relationship to one another. In some examples, position of a tag may be calculated by calculating multiple candidate positions using different localization techniques—such as geometric localization techniques and/or optimization-based techniques. An error may also be identified associated with each candidate position. A final position may be determined for the tag based on the errors associated with the candidate positions (e.g., the candidate position with the smallest error may be utilized as the position, e.g., the determined position, of the tag).