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Found 7 papers, 1 papers with code
Integrated Model Predictive Control of High-Speed Railway Running Gears with Driven Independently Rotating Wheels
Apart from lateral guidance, the longitudinal control is of crucial importance for railway safety.
VQF: Highly Accurate IMU Orientation Estimation with Bias Estimation and Magnetic Disturbance Rejection
Orientation estimation is a prerequisite for most further data processing steps in inertial motion tracking, such as position/velocity estimation, joint angle estimation, and 3D visualization.
RIANN -- A Robust Neural Network Outperforms Attitude Estimation Filters
We gather six publicly available datasets of which we exploit two datasets for the method development and the training, and we use four datasets for evaluation of the trained estimator in three different test scenarios with varying practical relevance.
Collective Iterative Learning Control: Exploiting Diversity in Multi-Agent Systems for Reference Tracking Tasks
We show that the proposed method allows the collective to combine the advantages of the agents' individual learning strategies and thereby overcomes trade-offs and limitations of single-agent ILC.
Observability of the relative motion from inertial data in kinematic chains
Real-time motion tracking of kinematic chains is a key prerequisite in the control of, e. g., robotic actuators and autonomous vehicles and also has numerous biomechanical applications.
Neural Networks Versus Conventional Filters for Inertial-Sensor-based Attitude Estimation
Inertial measurement units are commonly used to estimate the attitude of moving objects.
A Kernel Two-sample Test for Dynamical Systems
Evaluating whether data streams are drawn from the same distribution is at the heart of various machine learning problems.
