no code implementations • 25 Mar 2024 • Jonas Rothfuss, Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause
We present SIM-FSVGD for learning robot dynamics from data.
no code implementations • 13 Nov 2023 • Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause
We introduce PACOH-RL, a novel model-based Meta-Reinforcement Learning (Meta-RL) algorithm designed to efficiently adapt control policies to changing dynamics.
no code implementations • 15 Sep 2023 • Yue Li, Stelian Coros, Bernhard Thomaszewski
Nonlinear metamaterials with tailored mechanical properties have applications in engineering, medicine, robotics, and beyond.
1 code implementation • 13 Sep 2023 • Flavio De Vincenti, Stelian Coros
We present Ungar, an open-source library to aid the implementation of high-dimensional optimal control problems (OCPs).
1 code implementation • 12 Jun 2023 • Daniel Widmer, Dongho Kang, Bhavya Sukhija, Jonas Hübotter, Andreas Krause, Stelian Coros
This paper presents a data-driven strategy to streamline the deployment of model-based controllers in legged robotic hardware platforms.
no code implementations • 29 May 2023 • Dongho Kang, Jin Cheng, Miguel Zamora, Fatemeh Zargarbashi, Stelian Coros
These reference motions serve as targets for the RL policy to imitate, leading to the development of robust control policies that can be learned with reliability.
no code implementations • 16 Mar 2023 • Núria Armengol Urpí, Marco Bagatella, Otmar Hilliges, Georg Martius, Stelian Coros
Real-world robotic manipulation tasks remain an elusive challenge, since they involve both fine-grained environment interaction, as well as the ability to plan for long-horizon goals.
no code implementations • 9 Apr 2022 • Bhavya Sukhija, Nathanael Köhler, Miguel Zamora, Simon Zimmermann, Sebastian Curi, Andreas Krause, Stelian Coros
In our hardware experiments, we demonstrate that our learned model can represent complex dynamics for both the Spot and Radio-controlled (RC) car, and gives good performance in combination with trajectory optimization methods.
no code implementations • 7 Mar 2022 • Miguel Zamora, Roi Poranne, Stelian Coros
We formulate the learning of solution manifolds as a minimization of the energy terms of a control objective integrated over the space of problems of interest.
no code implementations • 3 Feb 2022 • Jeffrey Delmerico, Roi Poranne, Federica Bogo, Helen Oleynikova, Eric Vollenweider, Stelian Coros, Juan Nieto, Marc Pollefeys
Spatial computing -- the ability of devices to be aware of their surroundings and to represent this digitally -- offers novel capabilities in human-robot interaction.
1 code implementation • NeurIPS 2021 • Jonas Zehnder, Yue Li, Stelian Coros, Bernhard Thomaszewski
Recent advances in implicit neural representations show great promise when it comes to generating numerical solutions to partial differential equations.
no code implementations • 1 Jan 2021 • Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
Current reinforcement learning (RL) methods use simulation models as simple black-box oracles.
no code implementations • 25 Nov 2020 • Yue Li, Marc Habermann, Bernhard Thomaszewski, Stelian Coros, Thabo Beeler, Christian Theobalt
Recent monocular human performance capture approaches have shown compelling dense tracking results of the full body from a single RGB camera.
1 code implementation • 2 Jul 2020 • Moritz Geilinger, David Hahn, Jonas Zehnder, Moritz Bächer, Bernhard Thomaszewski, Stelian Coros
We present a differentiable dynamics solver that is able to handle frictional contact for rigid and deformable objects within a unified framework.