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Related papers: Dynamic Cloth Manipulation Considering Variable St…

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Materials used in real clothing exhibit remarkable complexity and spatial variation due to common processes such as stitching, hemming, dyeing, printing, padding, and bonding. Simulating these materials, for instance using finite element…

The capability to adapt compliance by varying muscle stiffness is crucial for dexterous manipulation skills in humans. Incorporating compliance in robot motor control is crucial to performing real-world force interaction tasks with…

Robotics · Computer Science 2023-09-28 Akhil S Anand , Fares J. Abu-Dakka , Jan Tommy Gravdahl

The complex behavior of highly deformable mechanical metamaterials can substantially enhance the performance of soft robots.

Soft Condensed Matter · Physics 2025-07-01 Ahmad Rafsanjani , Katia Bertoldi , André R. Studart

This work presents a framework for automatically extracting physical object properties, such as material composition, mass, volume, and stiffness, through robot manipulation and a database of object measurements. The framework involves…

Robot picking and packing tasks require dexterous manipulation skills, such as rearranging objects to establish a good grasping pose, or placing and pushing items to achieve tight packing. These tasks are challenging for robots due to the…

Robotics · Computer Science 2025-02-06 Kai Gao , Fan Wang , Erica Aduh , Dylan Randle , Jane Shi

Many soft-body organisms found in nature flourish underwater. Similarly, soft robots are potentially well-suited for underwater environments partly because the problematic effects of gravity, friction, and harmonic oscillations are less…

Robotics · Computer Science 2022-12-07 W. David Null , Y Z

In experimental robotics, researchers may face uncertainties in parameters of a robot manipulator that they are working with. This uncertainty may be caused by deviations in the manufacturing process of a manipulator, or changes applied to…

Systems and Control · Computer Science 2015-01-06 P. Mironchyk

An appropriate user interface to collect human demonstration data for deformable object manipulation has been mostly overlooked in the literature. We present an interaction design for demonstrating cloth folding to robots. Users choose pick…

Differentiable physics modeling combines physics models with gradient-based learning to provide model explicability and data efficiency. It has been used to learn dynamics, solve inverse problems and facilitate design, and is at its…

Machine Learning · Computer Science 2022-02-02 Deshan Gong , Zhanxing Zhu , Andrew J. Bulpitt , He Wang

Manipulation of deformable objects is a desired skill in making robots ubiquitous in manufacturing, service, healthcare, and security. Deformable objects are common in our daily lives, e.g., wires, clothes, bed sheets, etc., and are…

Robotics · Computer Science 2020-07-17 Peng Chang , Taskin Padir

Robot-assisted dressing is a popular but challenging topic in the field of robotic manipulation, offering significant potential to improve the quality of life for individuals with mobility limitations. Currently, the majority of research on…

Robotics · Computer Science 2025-08-19 Jian Zhao , Yunlong Lian , Andy M Tyrrell , Michael Gienger , Jihong Zhu

Lower limb amputations and neuromuscular impairments severely restrict mobility, necessitating advancements beyond conventional prosthetics. While motorized bionic limbs show promise, their effectiveness depends on replicating the dynamic…

Machine Learning · Computer Science 2025-06-06 Sharmita Dey , Benjamin Paassen , Sarath Ravindran Nair , Sabri Boughorbel , Arndt F. Schilling

Robots built from soft materials can alter their shape and size in a particular profile. This shape-changing ability could be extremely helpful for rescue robots and those operating in unknown terrains and environments. In changing shape,…

Robotics · Computer Science 2016-05-13 Vishesh Vikas , Eliad Cohen , Rob Grassi , Canberk Sozer , Barry Trimmer

Manipulating deformable objects has long been a challenge in robotics due to its high dimensional state representation and complex dynamics. Recent success in deep reinforcement learning provides a promising direction for learning to…

Robotics · Computer Science 2021-03-09 Xingyu Lin , Yufei Wang , Jake Olkin , David Held

Humans frequently grasp, manipulate, and move objects. Interactive systems assist humans in these tasks, enabling applications in Embodied AI, human-robot interaction, and virtual reality. However, current methods in hand-object synthesis…

Robotics · Computer Science 2025-03-10 Sammy Christen

We consider the setting of an agent with a fixed body interacting with an unknown and uncertain external world. We show that models trained to predict proprioceptive information about the agent's body come to represent objects in the…

In this paper, we propose a novel design of a hybrid mobile robot with controllable stiffness and deformable shape. Compared to conventional mobile agents, our system can switch between rigid and compliant phases by solidifying or melting…

Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning in recent years. One of the key challenges in manipulation is the exploration of the dynamics of the environment when…

Robotics · Computer Science 2022-10-25 Tim Schneider , Boris Belousov , Georgia Chalvatzaki , Diego Romeres , Devesh K. Jha , Jan Peters

Manipulating unseen objects is challenging without a 3D representation, as objects generally have occluded surfaces. This requires physical interaction with objects to build their internal representations. This paper presents an approach…

Robotics · Computer Science 2024-10-27 Saptarshi Dasgupta , Akshat Gupta , Shreshth Tuli , Rohan Paul

Robotic dressing assistance has the potential to improve the quality of life for individuals with limited mobility. Existing solutions predominantly rely on rigid robotic manipulators, which have challenges in handling deformable garments…

Robotics · Computer Science 2025-07-11 Nam Gyun Kim , William E. Heap , Yimeng Qin , Elvy B. Yao , Jee-Hwan Ryu , Allison M. Okamura
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