Adaptive Kalman Filtering for Compensating External Effects in On-Line Spectroscopic Measurements. [PDF]
Sbarbaro D, Johansen TA, Yañez J.
europepmc +1 more source
Research of the crankshaft high cycle bending fatigue experiment design method based on the modified unscented Kalman filtering algorithm and the SAFL approach. [PDF]
Rui S, Jiang D, Sun S, Gong X.
europepmc +1 more source
ABSTRACT This paper presents the development and validation of a scalable platooning system based on the predecessor‐following (PF) topology, designed for low‐cost follower platforms. It integrates key technologies such as localization, path planning, profile generation, and low‐level control to create a practical solution.
Dongwoo Seo, Jinhee Lee, Jaeyoung Kang
wiley +1 more source
Model-Based Control of a Continuum Manipulator with Online Jacobian Error Compensation Using Kalman Filtering. [PDF]
Zhai Y, Xu J, Mo H, Zhang C, Sun D.
europepmc +1 more source
POD-Kalman filtering for improving noninvasive 3D temperature monitoring in MR-guided hyperthermia. [PDF]
VilasBoas-Ribeiro I +7 more
europepmc +1 more source
ABSTRACT We present a comprehensive teleoperation framework for electric vehicle (EV) battery cell handling, integrating haptic feedback, extended reality (XR) visualization, and task‐parameterized Gaussian mixture regression (TP‐GMR) for adaptive, real‐time trajectory generation.
Alireza Rastegarpanah +5 more
wiley +1 more source
Velocity-Constraint Kalman Filtering for Enhanced Bubble Tracking in Motion-Compensated Ultrasound Localization Microscopy. [PDF]
Zhu Y +15 more
europepmc +1 more source
Bayesian inference of kinetic schemes for ion channels by Kalman filtering. [PDF]
Münch JL +3 more
europepmc +1 more source
A Robust Transformer–Based Error Compensation Method for Gyroscope of IMUs
ABSTRACT Inertial Measurement Units (IMUs), comprising gyroscopes and accelerometers, are fundamental for motion estimation in navigation and robotics. However, their performance is often degraded by nonlinear and time‐varying errors, such as bias drift, scale‐factor deviations, and sensor noise.
Xin Ye +4 more
wiley +1 more source
A Data Reconstruction Method for Inspection Mode in GBSAR Monitoring Using Sage-Husa Adaptive Kalman Filtering and RTS Smoothing. [PDF]
Qi Y +6 more
europepmc +1 more source

