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Physics-based simulation is essential for developing and evaluating robot manipulation policies, particularly in scenarios involving deformable objects and complex contact interactions. However, existing simulators often struggle to balance…

This paper presents a novel approach to numerically describe the interactions between rigid bodies, with a special focus on robotic grasping. Some of the more common approaches used to address such issues rely on satisfaction of a set of…

Robotics · Computer Science 2021-08-03 Michael Zechmair , Yannick Morel

We present a principled method for motion prediction via dynamic simulation for rigid bodies in intermittent contact with each other where the contact region is a planar non-convex contact patch. Such methods are useful in planning and…

Robotics · Computer Science 2020-10-08 Jiayin Xie , Nilanjan Chakraborty

With the maturation of differentiable physics, its role in various downstream applications: such as model predictive control, robotic design optimization, and neural PDE solvers, has become increasingly important. However, the derivative…

Robotics · Computer Science 2025-09-26 Xiaohan Ye , Kui Wu , Zherong Pan , Taku Komura

This article presents computationally efficient algorithms for modeling two special cases of rigid contact---contact with only viscous friction and contact without slip---that have particularly useful applications in robotic locomotion and…

Robotics · Computer Science 2015-04-06 Evan Drumwright

In recent years, an increasing amount of work has focused on differentiable physics simulation and has produced a set of open source projects such as Tiny Differentiable Simulator, Nimble Physics, diffTaichi, Brax, Warp, Dojo and DiffCoSim.…

Machine Learning · Computer Science 2022-07-13 Yaofeng Desmond Zhong , Jiequn Han , Georgia Olympia Brikis

Automating dexterous, contact-rich manipulation tasks using rigid robots is a significant challenge in robotics. Rigid robots, defined by their actuation through position commands, face issues of excessive contact forces due to their…

Robotics · Computer Science 2024-09-27 Tatsuya Kamijo , Cristian C. Beltran-Hernandez , Masashi Hamaya

We present a principled method for motion prediction via dynamic simulation for rigid bodies in intermittent contact with each other where the contact is assumed to be a planar non-convex contact patch. The planar non-convex contact patch…

Robotics · Computer Science 2019-04-18 Jiayin Xie , Nilanjan Chakraborty

A unified solution to adaptive approximation-based control for nonlinear systems with accurate and inaccurate state measurement is synthesized in this study. Starting from the standard adaptive approximation-based controller with accurate…

Systems and Control · Electrical Eng. & Systems 2023-06-06 Dong Zhao

This paper investigates the problem of efficient computation of physically consistent multi-contact behaviors. Recent work showed that under mild assumptions, the problem could be decomposed into simpler kinematic and centroidal dynamic…

Robotics · Computer Science 2021-02-19 Brahayam Ponton , Majid Khadiv , Avadesh Meduri , Ludovic Righetti

This paper presents a novel implicit scheme for the constraint resolution in real-time finite element simulations in the presence of contact and friction. Instead of using the standard motion correction scheme, we propose an iterative…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-13 Ziqiu Zeng , Hadrien Courtecuisse

Parallel implementation of numerical adaptive mesh refinement (AMR)strategies for solving 3D elastostatic contact mechanics problems is an essential step toward complex simulations that exceed current performance levels. This paper…

Numerical Analysis · Mathematics 2025-11-26 Alexandre Epalle , Isabelle Ramière , Guillaume Latu , Frédéric Lebon

We propose a novel and efficient lifting approach for the optimal control of rigid-body systems with contacts to improve the convergence properties of Newton-type methods. To relax the high nonlinearity, we consider the state, acceleration,…

Optimization and Control · Mathematics 2022-10-25 Sotaro Katayama , Toshiyuki Ohtsuka

This study addresses the challenge of low dexterity in teleoperation tasks caused by limited sensory feedback and visual occlusion. We propose a novel approach that integrates haptic feedback into teleoperation using the adaptive triggers…

Recently, the utilization of aerial manipulators for performing pushing tasks in non-destructive testing (NDT) applications has seen significant growth. Such operations entail physical interactions between the aerial robotic system and the…

Robotics · Computer Science 2024-02-28 Tong Hui , Eugenio Cuniato , Michael Pantic , Marco Tognon , Matteo Fumagalli , Roland Siegwart

Contact modeling plays a central role in motion planning, simulation, and control of legged robots, as legged locomotion is realized through contact. The two prevailing approaches to model the contact consider rigid and compliant premise at…

Robot interaction control is often limited to low dynamics or low flexibility, depending on whether an active or passive approach is chosen. In this work, we introduce a hybrid control scheme that combines the advantages of active and…

Robotics · Computer Science 2025-03-11 Christian Friedrich , Patrick Frank , Marco Santin , Matthias Haag

High-fidelity physics simulation is essential for scalable robotic learning, but the sim-to-real gap persists, especially for tasks involving complex, dynamic, and discontinuous interactions like physical contacts. Explicit system…

Robotics · Computer Science 2026-01-21 Changwei Jing , Jai Krishna Bandi , Jianglong Ye , Yan Duan , Pieter Abbeel , Xiaolong Wang , Sha Yi

There is invariably a trade-off between safety and efficiency for collaborative robots (cobots) in human-robot collaborations. Robots that interact minimally with humans can work with high speed and accuracy but cannot adapt to new tasks or…

Robotics · Computer Science 2022-10-13 Xiangjie Yan , Yongpeng Jiang , Chen Chen , Leiliang Gong , Ming Ge , Tao Zhang , Xiang Li

A realistic simulation environment is an essential tool in every roboticist's toolkit, with uses ranging from planning and control to training policies with reinforcement learning. Despite the centrality of simulation in modern robotics,…

Robotics · Computer Science 2022-07-18 Brian Acosta , William Yang , Michael Posa