5 papers
Estimation of Spacecraft Inertia Tensor Using Attitude-Only Data from Torque-Free Motion
Daigo Kobayashi, Vakhtang Putkaradze
We present an attitude-only framework for estimating a spacecraft's normalized inertia tensor from torque-free rotational motion. Our method supports both continuous single-arc obs…
The Neural Division of Labor: Biologically-Inspired Modular Architectures for Robust Neuromorphic Computing
Maksim Bazhenov, Serafim Grubas, Vakhtang Putkaradze
Biological neural systems achieve high efficiency and robustness through compartmentalized architectures. In contrast, modern artificial neural networks rely on globally entangled…
Latent Lie-Poisson Neural Networks (LLPNNs): Discovering the motion of Lie-Poisson systems through observable data and latent dynamics
Vakhtang Putkaradze
Structure-preserving neural networks are essential for the long-term prediction of Hamiltonian systems from data. Many important Hamiltonian systems in mechanics and control admit…
Variational Neural Networks for Observable Thermodynamics (V-NOTS)
Christopher Eldred, François Gay-Balmaz, Vakhtang Putkaradze
Much attention has recently been devoted to data-based computing of evolution of physical systems. In such approaches, information about data points from past trajectories in phase…
Structure-preserving learning and prediction in optimal control of collective motion
Sofiia Huraka, Vakhtang Putkaradze
Wide-spread adoption of unmanned vehicle technologies requires the ability to predict the motion of the combined vehicle operation from observations. While the general prediction o…