no code implementations • 10 Jun 2023 • Franck Djeumou, Cyrus Neary, Ufuk Topcu
We present a framework and algorithms to learn controlled dynamics models using neural stochastic differential equations (SDEs) -- SDEs whose drift and diffusion terms are both parametrized by neural networks.
no code implementations • 10 Jun 2023 • Franck Djeumou, Jonathan Y. M. Goh, Ufuk Topcu, Avinash Balachandran
Near the limits of adhesion, the forces generated by a tire are nonlinear and intricately coupled.
no code implementations • 9 Jan 2023 • Adam J. Thorpe, Cyrus Neary, Franck Djeumou, Meeko M. K. Oishi, Ufuk Topcu
Our proposed approach incorporates prior knowledge of the system dynamics as a bias term in the kernel learning problem.
1 code implementation • 30 Dec 2022 • Franck Djeumou, Christian Ellis, Murat Cubuktepe, Craig Lennon, Ufuk Topcu
First, they require an excessive amount of data due to the information asymmetry between the expert and the learner.
1 code implementation • 14 Jan 2022 • Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot, Ufuk Topcu
Neural ordinary differential equations (NODEs) -- parametrizations of differential equations using neural networks -- have shown tremendous promise in learning models of unknown continuous-time dynamical systems from data.
1 code implementation • 14 Sep 2021 • Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot, Ufuk Topcu
The physics-informed constraints are enforced via the augmented Lagrangian method during the model's training.
no code implementations • 29 Jun 2021 • Franck Djeumou, Zhe Xu, Murat Cubuktepe, Ufuk Topcu
Specifically, we study a setting in which the agents move along the nodes of a graph, and the high-level task specifications for the swarm are expressed in a recently-proposed language called graph temporal logic (GTL).
no code implementations • 19 Jun 2021 • Franck Djeumou, Ufuk Topcu
We develop a learning-based control algorithm for unknown dynamical systems under very severe data limitations.
no code implementations • 28 May 2021 • Franck Djeumou, Murat Cubuktepe, Craig Lennon, Ufuk Topcu
Nevertheless, the resulting formulation is still nonconvex due to the intrinsic nonconvexity of the so-called forward problem, i. e., computing an optimal policy given a reward function, in POMDPs.
no code implementations • 13 May 2021 • Christos K. Verginis, Franck Djeumou, Ufuk Topcu
We develop a control algorithm that ensures the safety, in terms of confinement in a set, of a system with unknown, 2nd-order nonlinear dynamics.
no code implementations • 11 Nov 2020 • Franck Djeumou, Abraham P. Vinod, Eric Goubault, Sylvie Putot, Ufuk Topcu
Besides, $\texttt{DaTaControl}$ achieves near-optimal control and is suitable for real-time control of such systems.
no code implementations • 27 Sep 2020 • Franck Djeumou, Abraham P. Vinod, Eric Goubault, Sylvie Putot, Ufuk Topcu
We investigate the problem of data-driven, on-the-fly control of systems with unknown nonlinear dynamics where data from only a single finite-horizon trajectory and possibly side information on the dynamics are available.