UTIL: An Ultra-wideband Time-difference-of-arrival Indoor Localization Dataset

TL;DR

UTIL addresses the lack of public datasets for UWB TDOA indoor localization by releasing a two-part dataset collected with low-cost DWM1000 modules. It combines LOS/NLOS identification data with a multimodal flight dataset totaling ~150 minutes of quadrotor operations across four anchor constellations, capturing UWB TDOA, IMU, optical flow, ToF, and millimeter-accurate ground truth. The authors provide a development kit and baseline benchmarks using ESKF and batch estimation, revealing ~10 cm RMSE in obstacle-free environments and highlighting localization challenges in cluttered and dynamic scenarios. This dataset enables measurement error modeling, fair comparisons of centralized vs decentralized TDOA, and the development of more robust UWB TDOA localization algorithms for real-world indoor settings.

Abstract

Ultra-wideband (UWB) time-difference-of-arrival (TDOA)-based localization has emerged as a promising, low-cost, and scalable indoor localization solution, which is especially suited for multi-robot applications. However, there is a lack of public datasets to study and benchmark UWB TDOA positioning technology in cluttered indoor environments. We fill in this gap by presenting a comprehensive dataset using Decawave's DWM1000 UWB modules. To characterize the UWB TDOA measurement performance under various line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, we collected signal-to-noise ratio (SNR), power difference values, and raw UWB TDOA measurements during the identification experiments. We also conducted a cumulative total of around 150 minutes of real-world flight experiments on a customized quadrotor platform to benchmark the UWB TDOA localization performance for mobile robots. The quadrotor was commanded to fly with an average speed of 0.45 m/s in both obstacle-free and cluttered environments using four different UWB anchor constellations. Raw sensor data including UWB TDOA, inertial measurement unit (IMU), optical flow, time-of-flight (ToF) laser altitude, and millimeter-accurate ground truth robot poses were collected during the flights. The dataset and development kit are available at https://utiasdsl.github.io/util-uwb-dataset/.

Figures (13)

• Figure 1: An UWB TDOA localization system in an indoor environment cluttered with wooden (blue boxes) and metal (the gray box) obstacles. UWB anchors are pre-installed with known positions in the space. The quadrotor, equipped with an UWB tag, receives TDOA measurements from the anchors for localization.
• Figure 2: The Loco Positioning System (LPS) anchor and tag from Bitcraze, based on Decawave's DWM1000 UWB modules, is used for the data collection.
• Figure 3: The sequence of UWB radio packets between the tag and anchor 1 and anchor 2. The clocks of anchor 1, anchor 2, and the tag are indicated as solid lines with different colors. The radio packets between the tag and anchors are denoted as solid arrow lines.
• Figure 4: UWB anchors and tag setup for UWB identification experiments.
• Figure 5: A diagram of the UWB identification experiments. The experiment process of LOS distance tests and LOS angle tests are illustrated in (a) and (b). The NLOS identification tests between an anchor and a tag and between two anchors are shown in (c) and (d).