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相关论文: Introducing Environmental Constraints to Grasping …

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Grasping a variety of objects remains a key challenge in the development of versatile robotic systems. The human hand is remarkably dexterous, capable of grasping and manipulating objects with diverse shapes, mechanical properties, and…

机器人学 · 计算机科学 2024-10-11 Ngoc-Duy Tran , Hoang-Hiep Ly , Xuan-Thuan Nguyen , Thi-Thoa Mac , Anh Nguyen , Tung D. Ta

Robot grasping is subject to an inherent tradeoff: Grippers with a large span typically take a longer time to close, and fast grippers usually cover a small span. However, many practical applications of soft grippers require the ability to…

机器人学 · 计算机科学 2023-10-03 Zechen Xiong , Zihan Guo , Li Yuan , Yufeng Su , Yitong Liu , Hod Lipson

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shape and surface properties remains, however, challenging. Most current…

Compliant and soft hands have gained a lot of attention in the past decade because of their ability to adapt to the shape of the objects, increasing their effectiveness for grasping. However, when it comes to grasping highly flexible…

机器人学 · 计算机科学 2020-04-10 Júlia Borràs , Guillem Alenya , Carme Torras

A shared grasp is a grasp formed by contacts between the manipulated object and both the robot hand and the environment. By trading off hand contacts for environmental contacts, a shared grasp requires fewer contacts with the hand, and…

机器人学 · 计算机科学 2020-06-05 Yifan Hou , Zhenzhong Jia , Matthew T. Mason

One of the trendsetting themes in soft robotics has been the goal of developing the ultimate universal soft robotic gripper. One that is capable of manipulating items of various shapes, sizes, thicknesses, textures, and weights. All the…

机器人学 · 计算机科学 2024-05-17 Ryo Kanno , Pham H. Nguyen , Joshua Pinskier , David Howard , Sukho Song , Mirko Kovac

Robotic manipulation of fresh fruits and vegetables, including the grasping of multiple loose items, has a strong industrial need but it still is a challenging task for robotic manipulation. This paper outlines the distinctive manipulation…

Endowing robots with tactile capabilities opens up new possibilities for their interaction with the environment, including the ability to handle fragile and/or soft objects. In this work, we equip the robot gripper with low-cost…

机器人学 · 计算机科学 2023-06-12 Michael C. Welle , Martina Lippi , Haofei Lu , Jens Lundell , Andrea Gasparri , Danica Kragic

Grasping objects with diverse mechanical properties, such as heavy, slippery, or fragile items, remains a significant challenge in robotics. Conventional rigid grippers typically rely on increasing the normal forces to secure an object,…

Robust grasping represents an essential task in robotics, necessitating tactile feedback and reactive grasping adjustments for robust grasping of objects. Previous research has extensively combined tactile sensing with grasping, primarily…

机器人学 · 计算机科学 2024-11-22 Yueming Hu , Mengde Li , Songhua Yang , Xuetao Li , Sheng Liu , Miao Li

Flexible object manipulation of paper and cloth is a major research challenge in robot manipulation. Although there have been efforts to develop hardware that enables specific actions and to realize a single action of paper folding using…

机器人学 · 计算机科学 2024-11-14 Yukina Iwata , Shun Hasegawa , Kento Kawaharazuka , Kei Okada , Masayuki Inaba

Robotic grasping is an essential capability, playing a critical role in enabling robots to physically interact with their surroundings. Despite extensive research, challenges remain due to the diverse shapes and properties of target…

机器人学 · 计算机科学 2025-04-03 Yeong Gwang Son , Seunghwan Um , Juyong Hong , Tat Hieu Bui , Hyouk Ryeol Choi

This paper tackles the task of singulating and grasping paper-like deformable objects. We refer to such tasks as paper-flipping. In contrast to manipulating deformable objects that lack compression strength (such as shirts and ropes), minor…

机器人学 · 计算机科学 2023-04-06 Chao Zhao , Chunli Jiang , Junhao Cai , Michael Yu Wang , Hongyu Yu , Qifeng Chen

Robots often face situations where grasping a goal object is desirable but not feasible due to other present objects preventing the grasp action. We present a deep Reinforcement Learning approach to learn grasping and pushing policies for…

机器人学 · 计算机科学 2024-03-19 Yongliang Wang , Kamal Mokhtar , Cock Heemskerk , Hamidreza Kasaei

Recently, suction-based robotic systems with microscopic features or active suction components have been proposed to grip rough and irregular surfaces. However, sophisticated fabrication methods or complex control systems are required for…

应用物理 · 物理学 2021-07-19 Sukho Song , Dirk-Michael Drotlef , Donghoon Son , Anastasia Koivikko , Metin Sitti

Mobile manipulation robots are continuously advancing, with their grasping capabilities rapidly progressing. However, there are still significant gaps preventing state-of-the-art mobile manipulators from widespread real-world deployments,…

This paper is a summary of the recently accomplished research work on flexible gripping systems. The goal is to develop a gripper which can be used for a great amount of geometrically variant workpieces. The economic aspect is of particular…

机器人学 · 计算机科学 2007-05-23 Michael Sdahl , Bernd Kuhlenkoetter

Novel robotic grippers have captured increasing interests recently because of their abilities to adapt to varieties of circumstances and their powerful functionalities. Differing from traditional gripper with mechanical components-made…

Grasping is an essential capability for most robots in practical applications. Soft robotic grippers are considered as a critical part of robotic grasping and have attracted considerable attention in terms of the advantages of the high…

机器人学 · 计算机科学 2021-11-09 Huixu Dong , Chao-Yu Chen , Chen Qiu , Chen-Hua Yeow , Haoyong Yu

Robotic grasping in cluttered environments is often infeasible due to obstacles preventing possible grasps. Then, pre-grasping manipulation like shifting or pushing an object becomes necessary. We developed an algorithm that can learn, in…

机器人学 · 计算机科学 2019-07-26 Lars Berscheid , Pascal Meißner , Torsten Kröger
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