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

TL;DR

This paper introduces a real-time framework for automatically detecting and calibrating unknown UWB anchors in navigation systems, enhancing robustness and accuracy in practical scenarios.

Contribution

The authors develop a novel method combining online PDOP estimation, outlier detection, and adaptive optimization for automatic anchor initialization during operation.

Findings

Improved robustness over state-of-the-art methods.

Lower initialization errors due to better geometry.

Validated on mobile robots with effective results.

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.