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UWB-Based Robot Localization Using Distributed Adaptive EFIR Filtering
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AI
DOI：10.1109/JIOT.2024.3414399.png)
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Abstract
En 中文
Ultrawideband (UWB)-based localization is widely used in environments inaccessible to global navigation satellite system signals. To improve the precision of UWB-based localization, a robust distributed adaptive extended unbiased finite impulse response (EFIR) filtering algorithm is developed. The algorithm is designed to reduce round-off errors and adaptively adjust noise covariances using the expectation-maximization (EM) approach. Based on extensive experimental testing, the EFIR algorithm is shown to outperform the distributed extended Kalman filter-based algorithm and distributed EFIR filter-based algorithm under harsh conditions.
Keywords:
Robots
Robot kinematics
Noise
Location awareness
Robot localization
Internet of Things
Accuracy
Distributed extended unbiased finite impulse response (EFIR) filter
expectation-maximization (EM)
robot localization
ultrawideband (UWB)
Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W