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

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