Publications associées à A Dynamical System for Online Learning of Periodic Movements of Unknown Waveform and Frequency

Publications associées (16)

Navigating the Loop: From Control Systems to Neural Networks and Back

The work presented in this thesis lies at the intersection of Machine Learning (ML) and control theory. The first part is dedicated to the design of Deep Neural Network (DNN) architectures with specific numerical properties, inspired by dynamical systems m ...

EPFL2024

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Colin Neil Jones, Wenjie Xu

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Elsevier Sci Ltd2024

Enhancing Dexterity in Confined Spaces: Real-Time Motion Planning for Multifingered In-Hand Manipulation

Aude Billard, Kunpeng Yao, Farshad Khadivar, Xiao Gao

Dexterous in-hand manipulation in robotics, particularly with multi-fingered robotic hands, poses significant challenges due to the intricate avoidance of collisions among fingers and the object being manipulated. Collision-free paths for all fingers must ...

2024

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Ursula Röthlisberger, Martin Peter Bircher, Justin Villard

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, wit ...

Royal Soc Chemistry2024

Koopman analysis of the periodic Korteweg-de Vries equation

Jeremy Peter Parker

The eigenspectrum of the Koopman operator enables the decomposition of nonlinear dynamics into a sum of nonlinear functions of the state space with purely exponential and sinusoidal time dependence. For a limited number of dynamical systems, it is possible ...

American Institute of Physics2023

Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control

Giancarlo Ferrari Trecate, John Lygeros, Luca Furieri, Andrea Martin

We consider control of dynamical systems through the lens of competitive analysis. Most prior work in this area focuses on minimizing regret, that is, the loss relative to an ideal clairvoyant policy that has noncausal access to past, present, and future d ...

Elsevier2023

Learning Linearized Degradation of Health Indicators using Deep Koopman Operator Approach

Olga Fink, Sergei Garmaev

With the current trend of increasing complexity of industrial systems, the construction and monitoring of health indicators becomes even more challenging. Given that health indicators are commonly employed to predict the end of life, a crucial criterion fo ...

Research Publishing2023

Topological Linear System Identification via Moderate Deviations Theory

Daniel Kuhn, Wouter Jongeneel, Tobias Sutter

Two dynamical systems are topologically equivalent when their phase-portraits can be morphed into each other by a homeomorphic coordinate transformation on the state space. The induced equivalence classes capture qualitative properties such as stability or ...

2022

Temperature- and pressure-dependence of the hydrogen bond network in plastic ice VII

Livia Eleonora Bove Kado, Umbertoluca Ranieri, Maria Rescigno

We model, via classical molecular dynamics simulations, the plastic phase of ice VII across a wide range of the phase diagram of interest for planetary investigations. Although structural and dynamical properties of plastic ice VII are mostly independent o ...

AIP Publishing2022

Variable Threshold Algorithm for Division of Labor Analyzed as a Dynamical System

Inaki Navarro Oiza

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Imitation learning of Globally Stable Non-Linear Point-to-Point Robot Motions using Nonlinear Programming

Aude Billard, Seyed Mohammad Khansari Zadeh

This paper presents a method to learn arbitrary discrete motions from a set of demonstrations. We model a motion as a nonlinear autonomous (i.e. time-invariant) dynamical system, and define the sufficient conditions to make such a system globally asymptoti ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Mode-specific reactivity of CH4 on Pt(110)-(1×2): The concerted role of stretch and bend excitation

Rainer Beck, Régis Bisson, Marco Sacchi

The state-resolved reaction probability of CH4 on Pt(110)-(1×2) was measured as a function of CH4 translational energy for four vibrational eigenstates comprising different amounts of C-H stretch and bend excitation. State-specific reactivity is observed b ...

American Physical Society2010

Movement Curvature Planning through Force Field Internal Models

Aude Billard, Biljana Petreska von Ritter-Zahony

Human motion studies have focused primarily on modeling straight point-to-point reaching movements. However, many goal-directed reaching movements, such as movements directed towards oneself, are not straight but rather follow highly curved trajectories. T ...

2009

On-line learning and modulation of periodic movements with nonlinear dynamical systems

Auke Ijspeert

The paper presents a two-layered system for (1) learning and encoding a periodic signal without any knowledge on its frequency and waveform, and (2) modulating the learned periodic trajectory in response to external events. The system is used to learn peri ...

2009

Reaching with Multi-Referential Dynamical Systems

Aude Billard, Micha Hersch

We study a reaching movement controller for a redundant serial arm manipulator, based on two principles believed to be central to biological motion control: multi-referential control and dynamical system control. The resulting controller is based on two co ...

2008

Dynamic simulation of regulatory networks using SQUAD

Giovanni De Micheli, Abhishek Garg

Background The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible t ...

2007