Anchor Signal Scheduling for Self-Localization Under Interference
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current localization systems for mobile robots are inadequate due to high communication latency, susceptibility to interference, and limited scalability, especially in environments where global navigation satellite systems are unreliable or multipath signals are prevalent, leading to reduced accuracy and robustness.
Innovation Solution
A self-localizing apparatus that uses timestampable signals, such as UWB signals, to determine its own position without emitting signals, allowing for higher update rates, improved accuracy, and increased robustness by optimizing transmission schedules and leveraging multiple transceivers for redundancy and interference mitigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized database architecture with tag emission is used for localization, then the system can maintain a centralized database of assets and their storage locations, but it introduces significant communication latency and higher risk of lost signals
Solution Approach 1:
Instead of having mobile robots emit signals and stationary sensors detect them (traditional approach), the patent inverts the architecture: stationary transceivers emit localization signals and mobile robots receive them. This inversion eliminates the need for mobile robots to transmit, reducing communication latency and improving system robustness while maintaining centralized database functionality.
2Quantity of substance
If multiple tags emit UWB signals at regular intervals, then the system can track multiple assets, but the maximum number of tags and tag emission rate are linked, limiting scalability
Solution Approach 1:
The patent inverts the traditional localization architecture by having stationary transceivers emit signals instead of mobile tags transmitting. This allows multiple stationary transceivers to serve numerous mobile robots simultaneously without increasing the emission rate burden on mobile devices, thereby decoupling the relationship between the number of tracked objects and the update rate.
Solution Approach 2:
Mobile robots equip their own receivers to autonomously receive and process localization signals from stationary transceivers, eliminating the need for centralized signal collection and processing. This self-service approach enables each mobile robot to independently determine its position at high update rates while the system scales to accommodate many more robots and tags.
3Measurement precision
If UWB sensors detect signals from tags and relay to a central server, then the system can compute tag locations, but it results in relatively higher risk of lost signals due to wireless interference
Solution Approach 1:
The patent inverts the signal flow direction: instead of mobile tags transmitting signals that must be detected by stationary sensors and relayed through a central server, stationary transceivers emit signals that mobile robots autonomously receive and process. This eliminates multiple relay points in the signal path, reducing the risk of signal loss from wireless interference while maintaining location computation accuracy.
4Adaptability or versatility
If current localization solutions are used in environments where GNSS is unreliable or multipath signals are prevalent, then the system can operate in diverse environments, but accuracy and robustness are reduced
Solution Approach 1:
The patent replaces GNSS satellite-based electromagnetic positioning with a terrestrial UWB localization system using stationary transceivers. This substitution provides reliable localization in GNSS-denied environments (indoor, underground, or areas with blockage) by using locally deployed transceivers that emit timestampable signals, achieving high accuracy even in multipath-prone environments through optimized signal processing and scheduling.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables mobile robots to operate with lower latency and higher accuracy, supporting more performant robot control and scalability, even in complex environments, while maintaining system robustness and privacy of operation.
Implementation Method 1
uses timestampable signals such as ultra-wideband (UWB) signals to determine its own position without emitting signals
Data Source
AI summary
Localization systems and methods for transmitting timestampable localization signals from anchors according to one or more transmission schedules. The transmission schedules may be generated and updated to achieve desired positioning performance. For example, one or more anchors may transmit localization signals at a different rate than other anchors, the anchor transmission order can be changed, and the signals can partially overlap. In addition, different transmission parameters may be used to transmit two localization signals at the same time without interference. A self-localizing apparatus is able to receive the localization signals and determine its position. The self-localizing apparatus may have a configurable receiver that can select to receive one of multiple available localization signals. The self-localizing apparatuses may have a pair of receivers able to receive two localization signals at the same time. A bridge anchor may be provided to enable a self-localizing apparatus to seamlessly transition between two localization systems.