Real-Time Initialization of Unknown Anchors for UWB-aided Navigation

2025-06-18

AI Summary

In UWB-aided navigation, unknown anchor positions typically require manual pre-deployment and lack dynamic, real-time initialization capability. Method: This paper proposes a real-time online anchor initialization method featuring a conservative triggering mechanism based on online Position Dilution of Precision (PDOP) estimation, integrated with lightweight anomaly detection and adaptive robust kernel-based nonlinear optimization for automatic anchor detection, geometric quality assessment, and calibration. A tightly coupled UWB/Visual-Inertial Odometry (VIO) localization framework is further developed and efficiently implemented in ROS C++. Contribution/Results: The method is validated on autonomous forklift and UWB-VIO quadrotor platforms, significantly improving initialization reliability and anchor geometry quality, while reducing localization error substantially. The source code is publicly available.

Technology Category

• Intelligent Robots: State Estimation
• Machine Learning: Calibration & Uncertainty Quantification
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

This paper presents a framework for the real-time initialization of unknown Ultra-Wideband (UWB) anchors in UWB-aided navigation systems. The method is designed for localization solutions where UWB modules act as supplementary sensors. Our approach enables the automatic detection and calibration of previously unknown anchors during operation, removing the need for manual setup. By combining an online Positional Dilution of Precision (PDOP) estimation, a lightweight outlier detection method, and an adaptive robust kernel for non-linear optimization, our approach significantly improves robustness and suitability for real-world applications compared to state-of-the-art. In particular, we show that our metric which triggers an initialization decision is more conservative than current ones commonly based on initial linear or non-linear initialization guesses. This allows for better initialization geometry and subsequently lower initialization errors. We demonstrate the proposed approach on two different mobile robots: an autonomous forklift and a quadcopter equipped with a UWB-aided Visual-Inertial Odometry (VIO) framework. The results highlight the effectiveness of the proposed method with robust initialization and low positioning error. We open-source our code in a C++ library including a ROS wrapper.

Problem

• Real-time initialization of unknown UWB anchors
• Automatic detection and calibration without manual setup
• Improves robustness in UWB-aided navigation systems

Innovation

• Real-time automatic UWB anchor detection
• Online PDOP and outlier detection
• Adaptive robust kernel optimization