首页|University of Toronto Researcher Details Research in Robotics (UTIL: An ultra-wideband time-difference-of-arrival indoor localization dataset)
University of Toronto Researcher Details Research in Robotics (UTIL: An ultra-wideband time-difference-of-arrival indoor localization dataset)
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New research on robotics is the subject of a new report. According to news reporting from Toronto, Canada, by NewsRx journalists, research stated, “Ultra-wideband (UWB) time-differenceof- arrival (TDOA)-based localization has emerged as a promising, low-cost, and scalable indoor localization solution, which is especially suited for multi-robot applications.” Our news correspondents obtained a quote from the research from University of Toronto: “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 min 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.”
University of TorontoTorontoCanadaNorth and Central AmericaEmerging TechnologiesMachine LearningRobotRobotics
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