首页|Study Findings from University of Technology Sydney Update Knowledge in Robotics (A Dynamic UKF-Based UWB/Wheel Odometry Tightly Coupled Approach for Indoor Pos itioning)
Study Findings from University of Technology Sydney Update Knowledge in Robotics (A Dynamic UKF-Based UWB/Wheel Odometry Tightly Coupled Approach for Indoor Pos itioning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Fresh data on robotics are presented i n a new report. According to news originating from Sydney, Australia, by NewsRx correspondents, research stated, “The centimetre-level accuracy of Ultra-wideban d (UWB) has attracted significant attention in indoor positioning.” The news journalists obtained a quote from the research from University of Techn ology Sydney: “However, the precision of UWB positioning is severely compromised by non-line-of-sight (NLOS) conditions that arise from complex indoor environme nts. On the other hand, odometry is widely applicable to wheeled robots due to i ts reliable short-term accuracy and high sampling frequency, but it suffers from long-term drift. This paper proposes a tightly coupled fusion method with a Dyn amic Unscented Kalman Filter (DUKF), which utilises odometry to identify and mit igate NLOS effects on UWB measurements. Horizontal Dilution of Precision (HDOP) was introduced to assess the impact of geometric distribution between robots and UWB anchors on UWB positioning accuracy. By dynamically adjusting UKF parameter s based on NLOS condition, HDOP values, and robot motion status, the proposed me thod achieves excellent UWB positioning results in a severe NLOS environment, wh ich enables UWB positioning even when only one line-of-sight (LOS) UWB anchor is available.”
University of Technology SydneySydneyAustraliaAustralia and New ZealandEmerging TechnologiesMachine LearningNano-robotRobotics
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