Search Results for author: Jean-Jacques E. Slotine

Found 15 papers, 3 papers with code

Coriolis Factorizations and their Connections to Riemannian Geometry

no code implementations22 Dec 2023 Patrick M. Wensing, Johannes Englsberger, Jean-Jacques E. Slotine

Many energy-based control strategies for mechanical systems require the choice of a Coriolis factorization satisfying a skew-symmetry property.

Adversarially Robust Stability Certificates can be Sample-Efficient

no code implementations20 Dec 2021 Thomas T. C. K. Zhang, Stephen Tu, Nicholas M. Boffi, Jean-Jacques E. Slotine, Nikolai Matni

Motivated by bridging the simulation to reality gap in the context of safety-critical systems, we consider learning adversarially robust stability certificates for unknown nonlinear dynamical systems.

Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview

no code implementations1 Oct 2021 Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

Contraction theory is an analytical tool to study differential dynamics of a non-autonomous (i. e., time-varying) nonlinear system under a contraction metric defined with a uniformly positive definite matrix, the existence of which results in a necessary and sufficient characterization of incremental exponential stability of multiple solution trajectories with respect to each other.


Nonparametric adaptive control and prediction: theory and randomized algorithms

no code implementations7 Jun 2021 Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

A key assumption in the theory of nonlinear adaptive control is that the uncertainty of the system can be expressed in the linear span of a set of known basis functions.

Adaptive Variants of Optimal Feedback Policies

no code implementations6 Apr 2021 Brett T. Lopez, Jean-Jacques E. Slotine

The stable combination of optimal feedback policies with online learning is studied in a new control-theoretic framework for uncertain nonlinear systems.

Transfer Learning

Universal Adaptive Control of Nonlinear Systems

no code implementations31 Dec 2020 Brett T. Lopez, Jean-Jacques E. Slotine

This work develops a new direct adaptive control framework that extends the certainty equivalence principle to general nonlinear systems with unmatched model uncertainties.

Motion Planning Transfer Learning

Regret Bounds for Adaptive Nonlinear Control

no code implementations26 Nov 2020 Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

We study the problem of adaptively controlling a known discrete-time nonlinear system subject to unmodeled disturbances.

Neural Stochastic Contraction Metrics for Learning-based Control and Estimation

1 code implementation6 Nov 2020 Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques E. Slotine

We present Neural Stochastic Contraction Metrics (NSCM), a new design framework for provably-stable robust control and estimation for a class of stochastic nonlinear systems.

Learning Stability Certificates from Data

no code implementations13 Aug 2020 Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani

Many existing tools in nonlinear control theory for establishing stability or safety of a dynamical system can be distilled to the construction of a certificate function that guarantees a desired property.

The role of optimization geometry in single neuron learning

no code implementations15 Jun 2020 Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

Recent numerical experiments have demonstrated that the choice of optimization geometry used during training can impact generalization performance when learning expressive nonlinear model classes such as deep neural networks.

Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization

1 code implementation29 Jul 2019 Sumeet Singh, Spencer M. Richards, Vikas Sindhwani, Jean-Jacques E. Slotine, Marco Pavone

We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics.

Continuous Control

A continuous-time analysis of distributed stochastic gradient

no code implementations28 Dec 2018 Nicholas M. Boffi, Jean-Jacques E. Slotine

We analyze the effect of synchronization on distributed stochastic gradient algorithms.

Distributed Optimization

A Geometric Characterization of Observability in Inertial Parameter Identification

3 code implementations10 Nov 2017 Patrick M. Wensing, Günter Niemeyer, Jean-Jacques E. Slotine

This paper presents an algorithm to geometrically characterize inertial parameter identifiability for an articulated robot.


Cannot find the paper you are looking for? You can Submit a new open access paper.