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Related papers: Push, Press, Slide: Mode-Aware Planar Contact Mani…

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Quasi-static models of robotic motion with frictional contact provide a computationally efficient framework for analysis and have been widely used for planning and control of non-prehensile manipulation. In this work, we present a novel…

Robotics · Computer Science 2019-02-12 Mathew Halm , Michael Posa

In this paper, we present the mechanics and algorithms to compute the set of feasible motions of an object pushed in a plane. This set is known as the motion cone and was previously described for non-prehensile manipulation tasks in the…

Robotics · Computer Science 2019-02-26 Nikhil Chavan-Dafle , Rachel Holladay , Alberto Rodriguez

Model-based planning in robotic domains is challenged by the hybrid nature of physical dynamics, where continuous motion is punctuated by discrete events such as contacts and impacts. Conventional latent world models typically employ…

Artificial Intelligence · Computer Science 2026-05-14 Mingwei Li , Xiaoyuan Zhang , Chengwei Yang , Zilong Zheng , Yaodong Yang

We present a controller for quasistatic robotic planar pushing with single-point contact using only force feedback to sense the pushed object. We consider an omnidirectional mobile robot pushing an object (the "slider") along a given path,…

Robotics · Computer Science 2024-06-19 Adam Heins , Angela P. Schoellig

In-hand object manipulation is an important capability for dexterous manipulation. In this paper, we introduce a modeling and planning framework for in-hand object reconfiguration, focusing on frictional patch contacts between the robot's…

Robotics · Computer Science 2024-10-22 An Dang , James Lorenz , Xili Yi , Nima Fazeli

This paper introduces a new technique for learning probabilistic models of mass and friction distributions of unknown objects, and performing robust sliding actions by using the learned models. The proposed method is executed in two…

Robotics · Computer Science 2020-08-06 Changkyu Song , Abdeslam Boularias

We introduce an approximate model for predicting the net contact wrench between nominally rigid objects for use in simulation, control, and state estimation. The model combines and generalizes two ideas: a bed of springs (an "elastic…

Computational Engineering, Finance, and Science · Computer Science 2019-08-07 Ryan Elandt , Evan Drumwright , Michael Sherman , Andy Ruina

Contact-rich bimanual manipulation involves precise coordination of two arms to change object states through strategically selected contacts and motions. Due to the inherent complexity of these tasks, acquiring sufficient demonstration data…

Robotics · Computer Science 2025-02-18 Xuanlin Li , Tong Zhao , Xinghao Zhu , Jiuguang Wang , Tao Pang , Kuan Fang

In this paper, we analyze the effects of contact models on contact-implicit trajectory optimization for manipulation. We consider three different approaches: (1) a contact model that is based on complementarity constraints, (2) a smooth…

Robotics · Computer Science 2019-01-31 Aykut Ozgun Onol , Philip Long , Taskin Padir

Non-prehensile (NP) manipulation, in which robots alter object states without forming stable grasps (for example, pushing, poking, or sliding), significantly broadens robotic manipulation capabilities when grasping is infeasible or…

Robotic in-hand manipulation has been a long-standing challenge due to the complexity of modelling hand and object in contact and of coordinating finger motion for complex manipulation sequences. To address these challenges, the majority of…

Robotics · Computer Science 2019-10-25 Tingguang Li , Krishnan Srinivasan , Max Qing-Hu Meng , Wenzhen Yuan , Jeannette Bohg

A robotic platform for mobile manipulation needs to satisfy two contradicting requirements for many real-world applications: A compact base is required to navigate through cluttered indoor environments, while the support needs to be large…

Friction plays a key role in manipulating objects. Most of what we do with our hands, and most of what robots do with their grippers, is based on the ability to control frictional forces. This paper aims to better understand the variability…

Robotics · Computer Science 2018-08-07 Daolin Ma , Alberto Rodriguez

This paper presents a reactive controller for planar manipulation tasks that leverages machine learning to achieve real-time performance. The approach is based on a Model Predictive Control (MPC) formulation, where the goal is to find an…

Robotics · Computer Science 2018-09-05 Francois Robert Hogan , Eudald Romo Grau , Alberto Rodriguez

This paper evaluates state-of-the-art contact models at predicting the motions and forces involved in simple in-hand robotic manipulations. In particular it focuses on three primitive actions --linear sliding, pivoting, and rolling-- that…

Robotics · Computer Science 2017-11-01 Roman Kolbert , Nikhil Chavan-Dafle , Alberto Rodriguez

Robotic manipulation in complex, constrained spaces is vital for widespread applications but challenging, particularly when navigating narrow passages with elongated objects. Existing planning methods often fail in these low-clearance…

Robotics · Computer Science 2025-11-10 Zihao Li , Yiming Zhu , Zhe Zhong , Qinyuan Ren , Yijiang Huang

We present in-hand manipulation tasks where a robot moves an object in grasp, maintains its external contact mode with the environment, and adjusts its in-hand pose simultaneously. The proposed manipulation task leads to complex contact…

Robotics · Computer Science 2024-03-29 Boyuan Liang , Kei Ota , Masayoshi Tomizuka , Devesh Jha

Parallel robots based on Handed Shearing Auxetics (HSAs) can implement complex motions using standard electric motors while maintaining the complete softness of the structure, thanks to specifically designed architected metamaterials.…

Robotics · Computer Science 2024-10-22 Maximilian Stölzle , Daniela Rus , Cosimo Della Santina

Industrial robotic object handling often involves boxes and packages whose mass and center of mass are not known in advance. These uncertainties affect the force--moment balance required for stable lifting, and improper regulation of…

Robotics · Computer Science 2026-05-22 Kenzhi Iskandar Wong , Lin Yang , Qian Ying Lee , Domenico Campolo

The empirical success of Reinforcement Learning (RL) in the setting of contact-rich manipulation leaves much to be understood from a model-based perspective, where the key difficulties are often attributed to (i) the explosion of contact…

Robotics · Computer Science 2023-03-01 Tao Pang , H. J. Terry Suh , Lujie Yang , Russ Tedrake