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

TL;DR

This paper introduces a novel UWB dataset that thoroughly analyzes how relative pose impacts UWB ranging measurements, providing precise ground-truth data to facilitate improved localization research.

Contribution

It presents the first dataset specifically designed to analyze the effects of relative pose on UWB ranging performance with accurate ground-truth poses.

Findings

Dataset enables detailed analysis of pose impact on UWB measurements

Provides precise ground-truth UWB poses for benchmarking

Facilitates improved understanding of UWB localization challenges

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 .