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A key challenge in robotics is to create efficient methods for grasping objects with diverse shapes, sizes, poses, and properties. Grasping with hand-like end effectors often requires careful selection of hand orientation and finger…

机器人学 · 计算机科学 2019-12-17 Yufei Hao , Shantonu Biswas , Elliot Hawkes , Tianmiao Wang , Mengjia Zhu , Li Wen , Yon Visell

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

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,…

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

In this paper, design and development of a sensor integrated adaptive gripper is presented. Adaptive grippers are useful for grasping objects of varied geometric shapes by wrapping fingers around the object. The finger closing sequence in…

机器人学 · 计算机科学 2020-08-28 IA Sainul , Sankha Deb , AK Deb

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

Biological systems, such as the octopus, exhibit masterful cross-scale manipulation by adaptively reconfiguring their entire form, a capability that remains elusive in robotics. Conventional soft grippers, while compliant, are mostly…

机器人学 · 计算机科学 2025-11-03 Dong Heon Han , Xiaohao Xu , Yuxi Chen , Yusheng Zhou , Xinqi Zhang , Jiaqi Wang , Daniel Bruder , Xiaonan Huang

Grasping mechanisms must both create and subsequently hold grasps that permit safe and effective object manipulation. Existing mechanisms address the different functional requirements of grasp creation and grasp holding using a single…

This study proposed a novel robotic gripper that can achieve grasping and infinite wrist twisting motions using a single actuator. The gripper is equipped with a differential gear mechanism that allows switching between the grasping and…

机器人学 · 计算机科学 2022-11-11 Toshihiro Nishimura , Yosuke Suzuki , Tokuo Tsuji , Tetsuyou Watanabe

Granular grippers are highly adaptable end-effectors that exploit the reversible jamming transition of granular materials to hold and manipulate objects. Their holding force comes from the combination of three mechanisms: frictional forces,…

软凝聚态物质 · 物理学 2025-04-09 Angel Santarossa , Olfa D'Angelo , Achim Sack , Thorsten Poeschel

Grasping objects with diverse mechanical properties, such as heavy, slippery, or fragile items, remains a significant challenge in robotics. Conventional grippers often rely on applying high normal forces, which can cause damage to objects.…

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…

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

Grasping using an aerial robot can have many applications ranging from infrastructure inspection and maintenance to precise agriculture. However, aerial grasping is a challenging problem since the robot has to maintain an accurate position…

机器人学 · 计算机科学 2023-11-03 Rishabh Dev Yadav , Brycen Jones , Saksham Gupta , Amitabh Sharma , Jiefeng Sun , Jianguo Zhao , Spandan Roy

This paper presents a soft robot finger capable of adaptive-twist deformation to grasp objects by wrapping them. For a soft hand to grasp and pick-up one object from densely contained multiple objects, a soft finger requires the…

机器人学 · 计算机科学 2025-10-29 Hiroki Ishikawa , Kyosuke Ishibashi , Ko Yamamoto

We propose a novel tri-fingered soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers adaptively conform to object shapes…

机器人学 · 计算机科学 2020-10-23 Dimuthu D. Arachchige , Yue Chen , Ian D. Walker , Isuru S. Godage

The application of granular jamming in soft robotics is a recent and promising new technology offer exciting possibilities for creating higher performance robotic devices. Granular jamming is achieved via the application of a vacuum…

Granular grippers can manipulate a wide variety of objects, but need to be pressed on the object to conform to it. If the object is placed on unstable ground, e.g., on sand or water, this step might cause the object to sink or move away…

软凝聚态物质 · 物理学 2024-04-25 Angel Santarossa , Olfa D'Angelo , Achim Sack , Thorsten Pöschel

Soft grippers have excellent adaptability for a variety of objects and tasks. Jamming-based variable stiffness materials can further increase soft grippers' gripping force and capacity. Previous universal grippers enabled by granular…

机器人学 · 计算机科学 2023-04-13 Yuchen Zhao , Yifan Wang

This paper presents a novel industrial robotic gripper with a high grasping speed (maximum: 1396 mm/s), high tip force (maximum: 80 N) for grasping, large motion range, and lightweight design (0.3 kg). To realize these features, the…

机器人学 · 计算机科学 2023-10-27 Toshihiro Nishimura , Takeshi Takaki , Yosuke Suzuki , Tokuo Tsuji , Tetsuyou Watanabe
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