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Simulation provides a cost-effective and flexible platform for data generation and policy learning to develop robotic systems. However, bridging the gap between simulation and real-world dynamics remains a significant challenge, especially…

Accurate simulation of soft mechanisms under dynamic actuation is critical for the design of soft robots. We address this gap with our differentiable simulation tool by learning the material parameters of our soft robotic fish. On the…

Due to their performance and simplicity, rigid body simulators are often used in applications where the objects of interest can considered very stiff. However, no material has infinite stiffness, which means there are potentially cases…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Aravind Ramakrishnan , David I. W. Levin , Alec Jacobson

In this paper we review the simulation method of the non-smooth contact dynamics. This technique was designed to solve the unilateral and frictional contact problem for a large number of rigid bodies and has proved to be especially valuable…

Soft Condensed Matter · Physics 2009-11-07 Tamas Unger , Janos Kertesz

Discrete particle simulations have become the standard in science and industrial applications exploring the properties of particulate systems. Most of such simulations rely on the concept of interacting spherical particles to describe the…

Numerical Analysis · Mathematics 2023-11-01 Igor Ostanin , Vasileios Angelidakis , Timo Plath , Sahar Pourandi , Anthony Thornton , Thomas Weinhart

Grasping is essential in robotic manipulation, yet challenging due to object and gripper diversity and real-world complexities. Traditional analytic approaches often have long optimization times, while data-driven methods struggle with…

Robotics · Computer Science 2024-12-16 Wenzheng Zhang , Fahira Afzal Maken , Tin Lai , Fabio Ramos

Robot learning requires a considerable amount of high-quality data to realize the promise of generalization. However, large data sets are costly to collect in the real world. Physics simulators can cheaply generate vast data sets with broad…

We propose a new model for the description of complex granular particles and their interaction in molecular dynamics simulations of granular material in two dimensions. The grains are composed of triangles which are connected by deformable…

adap-org · Physics 2012-08-29 Thorsten Poeschel , Volkhard Buchholtz

Coarse-graining has become an area of tremendous importance within many different research fields. For molecular simulation, coarse-graining bears the promise of finding simplified models such that long-time simulations of large-scale…

Chemical Physics · Physics 2019-09-04 Feliks Nüske , Lorenzo Boninsegna , Cecilia Clementi

In contrast with the diversity of materials found in nature, most robots are designed with some combination of aluminum, stainless steel, and 3D-printed filament. Additionally, robotic systems are typically assumed to follow basic…

Robotics · Computer Science 2025-03-04 Andrew K. Schulz , Ayah G. Ahmad , Maegan Tucker

The modern study of the dynamics of stellar systems requires the use of high-performance computers. Indeed, an accurate modelization of the structure and evolution of self-gravitating systems like planetary systems, open clusters, globular…

Astrophysics · Physics 2015-06-10 R. Capuzzo-Dolcetta , P. Di Matteo , P. Miocchi

Grasping deformable objects is not well researched due to the complexity in modelling and simulating the dynamic behavior of such objects. However, with the rapid development of physics-based simulators that support soft bodies, the…

Robotics · Computer Science 2021-07-20 Tran Nguyen Le , Jens Lundell , Fares J. Abu-Dakka , Ville Kyrki

Lattice spin models are useful for studying critical phenomena and allow the extraction of equilibrium and dynamical properties. Simulations of such systems are usually based on Monte Carlo (MC) techniques, and the main difficulty is often…

Computational Physics · Physics 2012-09-13 Tal Levy , Guy Cohen , Eran Rabani

We present a method for differentiable simulation of soft articulated bodies. Our work enables the integration of differentiable physical dynamics into gradient-based pipelines. We develop a top-down matrix assembly algorithm within…

Machine Learning · Computer Science 2022-05-05 Yi-Ling Qiao , Junbang Liang , Vladlen Koltun , Ming C. Lin

Nowadays, realistic simulation environments are essential to validate and build reliable robotic solutions. This is particularly true when using Reinforcement Learning (RL) based control policies. To this end, both robotics and RL…

Robotics · Computer Science 2023-10-12 Matteo El-Hariry , Antoine Richard , Miguel Olivares-Mendez

Autonomous robots must reason about the physical consequences of their actions to operate effectively in unstructured, real-world environments. We present Scan, Materialize, Simulate (SMS), a unified framework that combines 3D Gaussian…

Robotics · Computer Science 2025-05-22 Amine Elhafsi , Daniel Morton , Marco Pavone

Roadheader is an engineering robot widely used in underground engineering and mining industry. Interactive dynamics simulation of roadheader is a fundamental problem in unmanned excavation and virtual reality training. However, current…

Robotics · Computer Science 2022-10-04 Shengzhe Hou , Xinming Lu , Wenli Gao , Shuai Jiang , Xingli Zhang

Legged robot locomotion on sand slopes is challenging due to the complex dynamics of granular media and how the lack of solid surfaces can hinder locomotion. A promising strategy, inspired by ghost crabs and other organisms in nature, is to…

Robotics · Computer Science 2024-10-15 Haodi Hu , Feifei Qian , Daniel Seita

Granular segregation is ubiquitous in industrial, geological or daily-life context, but there is still no unifying theoretical approach. In this review, we examine two examples of granular segregation -- shallow rapid flows and rotating…

Soft Condensed Matter · Physics 2015-03-13 Matthias Schröter , Karen E. Daniels

The abundance of data has given machine learning considerable momentum in natural sciences and engineering, though modeling of physical processes is often difficult. A particularly tough problem is the efficient representation of geometric…

Machine Learning · Computer Science 2023-04-21 Andreas Mayr , Sebastian Lehner , Arno Mayrhofer , Christoph Kloss , Sepp Hochreiter , Johannes Brandstetter