3 citations · 3 across the 5 of their papers we have counts for
5 papers
Novel Algorithms for Smoothly Differentiable and Efficiently Vectorizable Contact Manifold Construction
Onur Beker, Andreas René Geist, Anselm Paulus +1
Generating intelligent robot behavior in contact-rich settings is a research problem where zeroth-order methods currently prevail. Developing methods that make use of first/second…
Differentiable Simulation of Hard Contacts with Soft Gradients for Learning and Control
Anselm Paulus, A. René Geist, Pierre Schumacher +3
Contact forces introduce discontinuities into robot dynamics that severely limit the use of simulators for gradient-based optimization. Penalty-based simulators such as MuJoCo, sof…
A Smooth Analytical Formulation of Collision Detection and Rigid Body Dynamics With Contact
Onur Beker, Nico Gürtler, Ji Shi +4
Generating intelligent robot behavior in contact-rich settings is a research problem where zeroth-order methods currently prevail. A major contributor to the success of such method…
Learning 3D-Gaussian Simulators from RGB Videos
Mikel Zhobro, Andreas René Geist, Georg Martius
Realistic simulation is critical for applications ranging from robotics to animation. Learned simulators have emerged as a possibility to capture real world physics directly from v…
Learning with 3D rotations, a hitchhiker's guide to SO(3)
A. René Geist, Jonas Frey, Mikel Zhobro +2
Many settings in machine learning require the selection of a rotation representation. However, choosing a suitable representation from the many available options is challenging. Th…