中文
相关论文

相关论文: Sim2Real Neural Controllers for Physics-based Robo…

200 篇论文

The deformable linear objects (DLOs) are common in both industrial and domestic applications, such as wires, cables, ropes. Because of its highly deformable nature, it is difficult for the robot to reproduce human's dexterous skills on…

机器人学 · 计算机科学 2021-07-02 Mingrui Yu , Hanzhong Zhong , Fangxun Zhong , Xiang Li

This paper addresses the problem of contact-based manipulation of deformable linear objects (DLOs) towards desired shapes with a dual-arm robotic system. To alleviate the burden of high-dimensional continuous state-action spaces, we model…

机器人学 · 计算机科学 2021-10-19 Shengzeng Huo , Anqing Duan , Chengxi Li , Peng Zhou , Wanyu Ma , David Navarro-Alarcon

Industrial assembly of deformable linear objects (DLOs) such as cables offers great potential for many industries. However, DLOs pose several challenges for robot-based automation due to the inherent complexity of deformation and,…

Autonomous wire harness assembly requires robots to manipulate complex branched cables with high precision and reliability. A key challenge in automating this process is predicting how these flexible and branched structures behave under…

机器人学 · 计算机科学 2025-05-07 Yizhou Chen , Xiaoyue Wu , Yeheng Zong , Yuzhen Chen , Anran Li , Bohao Zhang , Ram Vasudevan

We have seen much recent progress in rigid object manipulation, but interaction with deformable objects has notably lagged behind. Due to the large configuration space of deformable objects, solutions using traditional modelling approaches…

机器人学 · 计算机科学 2018-10-09 Jan Matas , Stephen James , Andrew J. Davison

This paper introduces a novel and general method to address the problem of using a general-purpose robot manipulator with a parallel gripper to wrap a deformable linear object (DLO), called a rope, around a rigid object, called a rod,…

机器人学 · 计算机科学 2023-04-12 Zhaoyuan Ma , Jing Xiao

Precise shape control of Deformable Linear Objects (DLOs) is crucial in robotic applications such as industrial and medical fields. However, existing methods face challenges in handling complex large deformation tasks, especially those…

机器人学 · 计算机科学 2026-02-26 Zhaowei Liang , Song Wang , Zhao Jin , Shirui Wu , Dan Wu

Manipulating deformable linear objects (DLOs) to achieve desired shapes in constrained environments with obstacles is a meaningful but challenging task. Global planning is necessary for such a highly-constrained task; however, accurate…

机器人学 · 计算机科学 2023-02-20 Mingrui Yu , Kangchen Lv , Changhao Wang , Masayoshi Tomizuka , Xiang Li

Deformable Linear Objects (DLOs) such as ropes and cables are widely encountered in both household and industrial applications, yet remain challenging to manipulate due to their infinite-dimensional configuration space and frequent…

机器人学 · 计算机科学 2026-05-18 Gina Wigginghaus , Tim Missal , Berk Guler , Simon Manschitz , Jan Peters

Robotic manipulation of deformable linear objects (DLOs) has great potential for applications in diverse fields such as agriculture or industry. However, a major challenge lies in acquiring accurate deformation models that describe the…

Deformable objects present several challenges to the field of robotic manipulation. One of the tasks that best encapsulates the difficulties arising due to non-rigid behavior is shape control, which requires driving an object to a desired…

The shape control of deformable linear objects (DLOs) is challenging, since it is difficult to obtain the deformation models. Previous studies often approximate the models in purely offline or online ways. In this paper, we propose a scheme…

机器人学 · 计算机科学 2022-02-17 Mingrui Yu , Hanzhong Zhong , Xiang Li

Manipulating Deformable Linear Objects (DLOs) is challenging in robotics due to their infinite-dimensional configuration space and complex nonlinear dynamics. In teleoperation, depth uncertainty hinders state perception and reaction.…

机器人学 · 计算机科学 2026-05-08 Berk Guler , Simon Manschitz , Kay Pompetzki , Jan Peters

Robotic manipulation of deformable 1D objects such as ropes, cables, and hoses is challenging due to the lack of high-fidelity analytic models and large configuration spaces. Furthermore, learning end-to-end manipulation policies directly…

Coordinated robotic manipulation of deformable linear objects (DLOs), such as ropes and cables, has been widely studied; however, handling hybrid assemblies composed of both deformable and rigid elements in constrained environments remains…

机器人学 · 计算机科学 2026-03-16 Anees Peringal , Anup Teejo Mathew , Panagiotis liatsis , Federico Renda

Long-horizon routing tasks of deformable linear objects (DLOs), such as cables and ropes, are common in industrial assembly lines and everyday life. These tasks are particularly challenging because they require robots to manipulate DLO with…

机器人学 · 计算机科学 2026-04-16 Mingen Li , Houjian Yu , Yixuan Huang , Youngjin Hong , Hantao Ye , Changhyun Choi

This work introduces an analytical approach for detecting and estimating external forces acting on deformable linear objects (DLOs) using only their observed shapes. In many robot-wire interaction tasks, contact occurs not at the…

机器人学 · 计算机科学 2026-02-03 Qi Jing Chen , Shilin Shan , Timothy Bretl , Quang-Cuong Pham

Humans are able to manipulate Deformable Linear Objects (DLOs) such as cables and wires, with little or no visual information, relying mostly on force sensing. In this work, we propose a reduced DLO model which enables such blind…

机器人学 · 计算机科学 2023-10-11 Finn Süberkrüb , Rita Laezza , Yiannis Karayiannidis

Tracing - estimating the spatial state of - long deformable linear objects such as cables, threads, hoses, or ropes, is useful for a broad range of tasks in homes, retail, factories, construction, transportation, and healthcare. For long…

The automatic shape control of deformable objects is a challenging (and currently hot) manipulation problem due to their high-dimensional geometric features and complex physical properties. In this study, a new methodology to manipulate…

机器人学 · 计算机科学 2021-04-12 Jiaming Qi , Guangfu Ma , Peng Zhou , Haibo Zhang , Yueyong Lyu , David Navarro-Alarcon