--- license: mit language: - en tags: - UAV - UWB - Ultra-Wideband - Positioning - Localization - Benchmark - Indoor - Outdoor - Machine Learning - Sensor Fusion - Robotics pretty_name: QDrone --- For additional details, please visit our website: https://benchmark.qdrone.ausmlab.com. # Q-Drone UWB Benchmark Dataset ## Overview We present a unique UWB benchmark dataset, called Q-Drone UWB benchmark. Q-Drone system, a UAV with UWB network built at York University, was used for acquiring this benchmark over five different sites, which include an indoor, open sports field, near to a building with glasses, semi-open tunnel and underneath bridge. The benchmark data were acquired by flying for a total of 1 h 50 min 28 sec flight time and about 4.3 km traveling distances with different maneuvering patterns and spatial configuration between UAV and UWB anchors as shown in the following table. ## Environments and Locations The data were collected from the following sites: - **Indoor:** Indoor environment, 26m(w) x 33m(l), Oshawa, Ontario, Canada - **Field:** Outdoor open sports field, 12m(w) x 13m(l), Uxbridge, Ontario, Canada - **Building:** Near a glass building, 7m(w) x 7m(l), Newmarket, Ontario, Canada - **Bridge:** Underneath a concrete-metal bridge, 10m(w) x 23m(l), Niagara, Ontario, Canada - **Tunnel:** Under a metal bridge, 8m(w) x 30m(l), Oshawa, Ontario, Canada ## Data Acquisition and Statistics ### Overall Dataset Characteristics | Site | Number of Datasets | Avg Data per Dataset | Flight Time (sec) | Travelled Distance (m) | Deployed UWB Anchors Area (m²) | UWB Range MAE (m) | |------------|--------------------|----------------------|-------------------|------------------------|---------------------------------|-------------------| | Indoor | 5 | 62194 | 1687 | 1260.88 | 91.96 | 0.37 | | Field | 5 | 92108 | 2313 | 1780.52 | 158.74 | 0.17 | | Building | 3 | 34007 | 823 | 388.92 | 50.10 | 2.02 | | Bridge | 4 | 26359 | 726 | 330.02 | 246.80 | 0.34 | | Tunnel | 6 | 39164 | 1079 | 504.47 | 241.80 | 1.61 | | **Total** | **23** | **253832** | **6628** | **4264.81** | **789.4** | **0.902** | ### Detailed Individual Dataset Information The specifics of data acquired per dataset include data points, IMU measurements, and precise coordinates of the UWB anchors for accurate localization. ## UAV Platform The UAV used in these experiments is the **DJI Matrice 100**, a professional UAV that supports mounting up to 2.4 kg payload. The payload includes a UWB tag, an Intel NUC computer, and a battery weighing 112, 728, and 542 grams, respectively. The DJI Matrice 100 is equipped with the following items: - **UWB TIME DOMAIN™ P440 UWB tag** - **Intel NUC computer** - **Prism GRZ101, 360° mini prism** - **External battery** ## UWB Anchor System **TIME DOMAIN** previously developed an Ultra-Wideband (UWB) radio transceiver named P400. For this experiment, we used a total of 5 PulsON 440 (P440) modules, which belong to the P400 family. The UWB anchors consist of four UWB tags mounted on tripods at various heights arranged in a square on the ground. The Time-of-Flight (TOF) method provides distance measurements between two or more sensors with 2 cm accuracy and up to 125 Hz rate. It operates in temperatures ranging from above 40°C to below -85°C, suitable for high shock and vibration environments. ## Total Station To ensure reliable data for validating position methods, we used a robotic total station. A GRZ101, 360° mini prism is mounted on the UAV, and the total station tracks it using modulated infrared light waves. The GRZ101 offers excellent pointing accuracy of 1.5 mm. For indoor, bridge, and tunnel datasets, we utilized the Leica Nova MS60 MultiStation, which measures ranges up to 1000m with 1” (0.00027°) angle accuracy. For outdoor datasets, the Trimble VX Spatial Station measures up to 5,500 m with 4 mm accuracy and 0.4 sec measurement time. ## Communication System The flight platform of the DJI Matrice 100 is customizable through an onboard SDK. The mounted NUC computer is connected to the Micro-USB port on the UAV. The SDK enables communication between the computer and the flight controller, as well as onboard sensors. IMU data is fed online to the computer through this SDK. Other mounted sensors include a UWB tag connected via USB to the computer, transmitting data including ranges between the UAV-mounted UWB antenna and four ground antennas. A prism mounted on the UAV measures XYZ using the total station. ## Data Format The data are available in **csv** format. Each file provides: - **IMU**: angular velocity -x, -y, -z; linear acceleration -x, -y, -z; orientation quaternion -x, -y, -z, -w; height value - **UWB**: Time(sec), Module ID, Range Calibration is not applied, and the data is raw in the UWB anchors coordination system. Each dataset includes optional correction coefficients. A preview of each trajectory is available. Synchronized video of most datasets helps visualize the effect of the environment and flight conditions on data variation. ## Structure of Dataset: ### UWB Data - **[row 1]** 0 - **[row 2]** Time(sec), Module ID, Range, Self-range error ### IMU Data - **[row 1]** 2 - **[row 2]** Time(sec), angular velocity-x, angular velocity-y, angular velocity-z, linear acc-x, linear acc-y, linear acc-z, orientation quaternion-x, orientation quaternion-y, orientation quaternion-z, orientation quaternion-w ### Height - **[row 1]** 3 - **[row 2]** Height value ## Conclusion This comprehensive dataset aims to aid in the development of UWB technologies by providing diverse scenarios and extensive benchmark data for performance testing under different environmental conditions. ## Citation: | **Please Cite Our Work**: If you use this dataset for your research, we kindly ask you to cite the following paper: > @inproceedings{arjmandi2020uwb, > title={Benchmark Dataset of Ultra-Wideband Radio Based UAV Positioning}, > author={Arjmandi, Zahra and Kang, Jungwon and Park, Sohn Kunwoo and Gunho}, > booktitle={IEEE International Conference on Intelligent Transportation Systems}, > year={2020} > }