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Dexterous manipulation through imitation learning has gained significant attention in robotics research. The collection of high-quality expert data holds paramount importance when using imitation learning. The existing approaches for…

Robotics · Computer Science 2023-09-27 Dehao Wei , Huazhe Xu

Stable and reliable grasp is critical to robotic manipulations especially for fragile and glazed objects, where the grasp force requires precise control as too large force possibly damages the objects while small force leads to slip and…

Robotics · Computer Science 2026-03-20 Chengxiao He , Wenhui Yang , Hongliang Zhao , Jiacheng Lv , Yuzhe Shao , Longhui Qin

Aerial manipulation requires force-aware capabilities to enable safe and effective grasping and physical interaction. Previous works often rely on heavy, expensive force sensors unsuitable for typical quadrotor platforms, or perform…

Robotics · Computer Science 2026-02-10 Kenghou Hoi , Yuze Wu , Annan Ding , Junjie Wang , Anke Zhao , Chengqian Zhang , Fei Gao

The sense of touch plays a key role in enabling humans to understand and interact with surrounding environments. For robots, tactile sensing is also irreplaceable. While interacting with objects, tactile sensing provides useful information…

Robotics · Computer Science 2021-12-30 Jiaqi Jiang , Shan Luo

We want to build robots that are useful in unstructured real world applications, such as doing work in the household. Grasping in particular is an important skill in this domain, yet it remains a challenge. One of the key hurdles is…

Robotics · Computer Science 2017-11-21 Ulrich Viereck , Andreas ten Pas , Kate Saenko , Robert Platt

The manipulation of garments poses research challenges due to their deformable nature and the extensive variability in shapes and sizes. Despite numerous attempts by researchers to address these via approaches involving robot perception and…

Robotics · Computer Science 2024-01-22 Dongmyoung Lee , Wei Chen , Xiaoshuai Chen , Nicolas Rojas

In recent years, advancements in optical tactile sensor technology have primarily centred on enhancing sensing precision and expanding the range of sensing modalities. To meet the requirements for more skilful manipulation, there should be…

Robotics · Computer Science 2025-02-04 Xuyang Zhang , Jiaqi Jiang , Shan Luo

Tactile sensing allows robots to gather detailed geometric information about objects through physical interaction, complementing vision-based approaches. However, efficiently acquiring useful tactile data remains challenging due to the…

Robotics · Computer Science 2026-02-27 Chung Hee Kim , Shivani Kamtikar , Tye Brady , Taskin Padir , Joshua Migdal

Sensing contacts throughout the fingers is an essential capability for a robot to perform manipulation tasks in cluttered environments. However, existing tactile sensors either only have a flat sensing surface or a compliant tip with a…

Robotics · Computer Science 2021-02-26 Daniel Fernandes Gomes , Zhonglin Lin , Shan Luo

Wearable biosensor technology enables real-time, convenient, and continuous monitoring of users behavioral signals. Such include signals relative to body motion, body temperature, biological or biochemical markers, and individual grip…

This work proposes a novel generative design tool for passive grippers -- robot end effectors that have no additional actuation and instead leverage the existing degrees of freedom in a robotic arm to perform grasping tasks. Passive…

Graphics · Computer Science 2023-06-07 Milin Kodnongbua , Ian Good Yu Lou , Jeffrey Lipton , Adriana Schulz

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,…

Robotics · Computer Science 2023-04-12 Zhaoyuan Ma , Jing Xiao

For humans, the process of grasping an object relies heavily on rich tactile feedback. Most recent robotic grasping work, however, has been based only on visual input, and thus cannot easily benefit from feedback after initiating contact.…

This work presents a next-generation human-robot interface that can infer and realize the user's manipulation intention via sight only. Specifically, we develop a system that integrates near-eye-tracking and robotic manipulation to enable…

Robotics · Computer Science 2023-05-16 Shaochen Wang , Wei Zhang , Zhangli Zhou , Jiaxi Cao , Ziyang Chen , Kang Chen , Bin Li , Zhen Kan

Manipulating fragile objects in environments such as homes and factories requires stable and gentle grasping along with precise and safe placement. Compared to traditional rigid grippers, the use of soft grippers reduces the control…

Robotics · Computer Science 2024-10-07 Xuyang Zhang , Tianqi Yang , Dandan Zhang , Nathan F. Lepora

This work describes the development of a high-resolution tactile-sensing finger for robot grasping. This finger, inspired by previous GelSight sensing techniques, features an integration that is slimmer, more robust, and with more…

Robotics · Computer Science 2018-05-16 Elliott Donlon , Siyuan Dong , Melody Liu , Jianhua Li , Edward Adelson , Alberto Rodriguez

Soft robotic grippers are shown to be high effective for grasping unstructured objects with simple sensing and control strategies. However, they are still limited by their speed, sensing capabilities and actuation mechanism. Hence, their…

In this paper, we propose an approach to detect incipient slip, i.e. predict slip, by using a high-resolution vision-based tactile sensor, GelSlim. The sensor dynamically captures the tactile imprints of the contact object and their changes…

Robotics · Computer Science 2018-11-01 Siyuan Dong , Daolin Ma , Elliott Donlon , Alberto Rodriguez

Locating and grasping of objects by robots is typically performed using visual sensors. Haptic feedback from contacts with the environment is only secondary if present at all. In this work, we explored an extreme case of searching for and…

Robotics · Computer Science 2026-03-05 Karel Bartunek , Lukas Rustler , Matej Hoffmann

Current approaches to grasp planning for robotics demonstrate high success rates, but degrade with noisy sensors and other factors. Previous works have proposed tactile-based grasp stability classifiers to detect failures, but these…

Robotics · Computer Science 2026-05-08 Kyle DuFrene , Cindy Grimm
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