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For many robotic manipulation and contact tasks, it is crucial to accurately estimate uncertain object poses, for which certain geometry and sensor information are fused in some optimal fashion. Previous results for this problem primarily…

Robotics · Computer Science 2023-05-29 Jeongmin Lee , Minji Lee , Dongjun Lee

This paper proposes a new method for manipulating unknown objects through a sequence of non-prehensile actions that displace an object from its initial configuration to a given goal configuration on a flat surface. The proposed method…

Robotics · Computer Science 2020-05-13 Changkyu Song , Abdeslam Boularias

We propose a new technique for pushing an unknown object from an initial configuration to a goal configuration with stability constraints. The proposed method leverages recent progress in differentiable physics models to learn unknown…

Robotics · Computer Science 2020-06-05 Changkyu Song , Abdeslam Boularias

Differentiable simulation establishes the mathematical foundation for solving challenging inverse problems in computer graphics and robotics, such as physical system identification and inverse dynamics control. However, rigor in frictional…

Graphics · Computer Science 2026-05-19 Ziqiu Zeng , Gang Yang , Zhenhao Huang , Bingyang Zhou , Yulin Li , Jason Pho , Siyuan Luo , Fan Shi

Precise perception of contact interactions is essential for fine-grained manipulation skills for robots. In this paper, we present the design of feedback skills for robots that must learn to stack complex-shaped objects on top of each other…

Many robot manipulation tasks require the robot to make and break contact with objects and surfaces. The dynamics of such changing-contact robot manipulation tasks are discontinuous when contact is made or broken, and continuous elsewhere.…

Robotics · Computer Science 2021-06-22 Saif Sidhik , Mohan Sridharan , Dirk Ruiken

Differentiable physics is a powerful tool in computer vision and robotics for scene understanding and reasoning about interactions. Existing approaches have frequently been limited to objects with simple shape or shapes that are known in…

Computer Vision and Pattern Recognition · Computer Science 2022-01-11 Michael Strecke , Joerg Stueckler

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

We present a differentiable dynamics solver that is able to handle frictional contact for rigid and deformable objects within a unified framework. Through a principled mollification of normal and tangential contact forces, our method…

Stably placing an object in a multi-object scene is a fundamental challenge in robotic manipulation, as placements must be penetration-free, establish precise surface contact, and result in a force equilibrium. To assess stability, existing…

Robotics · Computer Science 2025-09-29 Philippe Nadeau , Miguel Rogel , Ivan Bilić , Ivan Petrović , Jonathan Kelly

This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrinsic sensor measurements,…

State-of-the-art object pose estimation methods are prone to generating geometrically infeasible pose hypotheses. This problem is prevalent in dexterous manipulation, where estimated poses often intersect with the robotic hand or are not…

Robotics · Computer Science 2026-03-24 Anil Zeybek , Rhys Newbury , Snehal Dikhale , Nawid Jamali , Soshi Iba , Akansel Cosgun

Differentiable simulators promise to improve sample efficiency in robot learning by providing analytic gradients of the system dynamics. Yet, their application to contact-rich tasks like locomotion is complicated by the inherently…

Robotic manipulation can greatly benefit from the data efficiency, robustness, and predictability of model-based methods if robots can quickly generate models of novel objects they encounter. This is especially difficult when effects like…

Robotics · Computer Science 2023-10-19 Bibit Bianchini , Mathew Halm , Michael Posa

We introduce a planner designed to guide robot manipulators in stably placing objects within intricate scenes. Our proposed method reverses the traditional approach to object placement: our planner selects contact points first and then…

Robotics · Computer Science 2025-06-25 Philippe Nadeau , Jonathan Kelly

We study the problem of rapidly identifying contact dynamics of unknown objects in partially known environments. The key innovation of our method is a novel formulation of the contact dynamics estimation problem as the joint estimation of…

Robotics · Computer Science 2024-09-27 Jinhoo Kim , Yifan Zhu , Aaron Dollar

In this work, we build on our method for manipulating unknown objects via contact configuration regulation: the estimation and control of the location, geometry, and mode of all contacts between the robot, object, and environment. We…

Robotics · Computer Science 2023-10-03 Orion Taylor , Neel Doshi , Alberto Rodriguez

Manipulating deformable objects arises in daily life and numerous applications. Despite phenomenal advances in industrial robotics, manipulation of deformable objects remains mostly a manual task. This is because of the high number of…

Robotics · Computer Science 2024-01-31 Burak Aksoy , John Wen

This work establishes a solution to the problem of assessing the capacity of multi-object assemblies to withstand external forces without becoming unstable. Our physically-grounded approach handles arbitrary structures made from rigid…

Robotics · Computer Science 2025-06-25 Philippe Nadeau , Jonathan Kelly

Dexterous grasping of unseen objects in dynamic environments is an essential prerequisite for the advanced manipulation of autonomous robots. Prior advances rely on several assumptions that simplify the setup, including environment…

Robotics · Computer Science 2024-04-09 Yannick Burkhardt , Qian Feng , Jianxiang Feng , Karan Sharma , Zhaopeng Chen , Alois Knoll
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