Addressing Relative Pose Impact on UWB Localization: Dataset Introduction and Analysis

TL;DR

The paper addresses how relative pose between UWB tags and anchors biases ranging measurements, a factor often overlooked in UWB localization studies. It introduces a motion-capture-backed dataset with ground-truth 6-DOF relative poses and a single UWB tag to systematically analyze pose-dependent bias across six designed sequences. A bias model is presented, showing that dominant factors are the angular terms $\bm{\alpha}$, $\bm{\beta}$, and the heading difference $\bm{\gamma}$, with biases that diminish as range grows, enabling more accurate localization calibration. The dataset, freely accessible, provides a valuable resource for evaluating and correcting pose-induced biases in UWB-based robotics and autonomous systems, with planned outdoor data to broaden realism under challenging conditions.

Abstract

UWB has recently gained new attention as an auxiliary sensor in the field of robot localization due to its compactness and ease of distance measurement. Consequently, various UWB-related localization and dataset research have increased. Despite this broad interest, there is a lack of UWB datasets that thoroughly analyze the performance of UWB ranging measurement. To address this issue, our paper introduces a UWB dataset that examines UWB relative pose factors affecting ranging measurement. To the best of our knowledge, our dataset is the first to analyze these factors while rigorously providing precise ground-truth UWB poses. The dataset is accessible at https://github.com/cjhhalla/RCV_uwb_dataset .

Figures (4)

• Figure 1: Two synchronized monocular global shutter cameras, along with an IMU and a DW1000-based UWB tag extended on a rod, are mounted on the drone. The UWB is equipped with a rigid body frame, which determines the UWB's coordinate system. In the coordinate system, the UWB's origin is the center of the UWB device chip. Additionally, the coordinate axes are constructed following the right-hand rule. We adopt a single tag to avoid obstructing the signal path between the ranging measurement pairs. The upper right figure shows our experimental environment.
• Figure 2: Each trajectory sequence is recorded from the drone's takeoff to its landing with different anchor placements. Darker and brighter colors indicate takeoff and landing, respectively. The static anchors have their respective heading directions and are at the same height in Sequences 1 and 2, whereas in the other sequences, the anchor heights vary. The red arrows in the trajectory demonstrate the drone's heading direction.
• Figure 3: Notation of the relative pose between tag $T$ and anchor $A$: ranging measurement $\tilde{d}$, azimuth angle $\alpha_A$ and $\alpha_B$, elevation angle $\beta_A$ and $\beta_B$, and the difference angle $\gamma$, which represents the difference in heading angles.
• Figure 4: UWB ranging bias patterns affected by bias factors ($\tilde{d}$ ,$\alpha$, $\beta$, $\gamma$) across different sequences. Each sequence focuses on one bias factor for analysis.