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Related papers: Force/Torque Sensing for Soft Grippers using an Ex…

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Estimation of a hand grip force is essential for the understanding of force pattern during the execution of assembly or disassembly operations. Human demonstration of a correct way of doing an operation is a powerful source of information…

Robotics · Computer Science 2018-03-06 Andrey Sartison , Dima Mironov , Kamal Youcef-Toumi , Dzmitry Tsetserukou

We present a self-contained, soft robotic hand composed of soft pneumatic actuator modules that are equipped with strain and pressure sensing. We show how this data can be used to discern whether a grasp was successful. Co-locating sensing…

Robotics · Computer Science 2016-05-03 Nicholas Farrow , Yang Li , Nikolaus Correll

Reliable robotic grasping, especially with deformable objects such as fruits, remains a challenging task due to underactuated contact interactions with a gripper, unknown object dynamics and geometries. In this study, we propose a…

Robotics · Computer Science 2023-07-25 Yunhai Han , Kelin Yu , Rahul Batra , Nathan Boyd , Chaitanya Mehta , Tuo Zhao , Yu She , Seth Hutchinson , Ye Zhao

Properly handling delicate produce with robotic manipulators is a major part of the future role of automation in agricultural harvesting and processing. Grasping with the correct amount of force is crucial in not only ensuring proper grip…

Robotics · Computer Science 2026-02-05 Preston Fairchild , Claudia Chen , Xiaobo Tan

Grasping objects whose physical properties are unknown is still a great challenge in robotics. Most solutions rely entirely on visual data to plan the best grasping strategy. However, to match human abilities and be able to reliably pick…

Robotics · Computer Science 2021-09-24 Pietro Griffa , Carmelo Sferrazza , Raffaello D'Andrea

Current methods for estimating force from tactile sensor signals are either inaccurate analytic models or task-specific learned models. In this paper, we explore learning a robust model that maps tactile sensor signals to force. We…

Due to the complexity of modeling the elastic properties of materials, the use of machine learning algorithms is continuously increasing for tactile sensing applications. Recent advances in deep neural networks applied to computer vision…

Robotics · Computer Science 2020-06-05 Carmelo Sferrazza , Raffaello D'Andrea

Existing grasp controllers usually either only support finger-tip grasps or need explicit configuration of the inner forces. We propose a novel grasp controller that supports arbitrary grasp types, including power grasps with…

Robotics · Computer Science 2024-09-20 Dominik Winkelbauer , Rudolph Triebel , Berthold Bäuml

The most common sensing modalities found in a robot perception system are vision and touch, which together can provide global and highly localized data for manipulation. However, these sensing modalities often fail to adequately capture the…

Robotics · Computer Science 2022-04-20 Jessica Yin , Gregory M. Campbell , James Pikul , Mark Yim

Humans make extensive use of vision and touch as complementary senses, with vision providing global information about the scene and touch measuring local information during manipulation without suffering from occlusions. While prior work…

Robotics · Computer Science 2023-08-01 Justin Kerr , Huang Huang , Albert Wilcox , Ryan Hoque , Jeffrey Ichnowski , Roberto Calandra , Ken Goldberg

Compared to traditional rigid robotics, soft robotics has attracted increasing attention due to its advantages as compliance, safety, and low cost. As an essential part of soft robotics, the soft robotic gripper also shows its superior…

Robotics · Computer Science 2021-12-30 Xing Wang , Hanwen Kang , Hongyu Zhou , Wesley Au , Chao Chen

This paper proposes techniques to calibrate six-axis force-torque sensors that can be performed in situ, i.e., without removing the sensor from the hosting system. We assume that the force-torque sensor is attached to a rigid body equipped…

Robotics · Computer Science 2016-10-24 Silvio Traversaro , Daniele Pucci , Francesco Nori

The development of tactile sensing and its fusion with computer vision is expected to enhance robotic systems in handling complex tasks like deformable object manipulation. However, readily available industrial grippers typically lack…

Robotics · Computer Science 2023-06-12 Remko Proesmans , Francis wyffels

Soft tissue manipulation is an integral aspect of most surgical procedures; however, the vast majority of surgical graspers used today are made of hard materials, such as metals or hard plastics. Furthermore, these graspers predominately…

Robotics · Computer Science 2025-01-15 Roman Mykhailyshyn , Ann Majewicz Fey

Accurate 3D pose estimation of grasped objects is an important prerequisite for robots to perform assembly or in-hand manipulation tasks, but object occlusion by the robot's own hand greatly increases the difficulty of this perceptual task.…

Tactile sensing has become a popular sensing modality for robot manipulators, due to the promise of providing robots with the ability to measure the rich contact information that gets transmitted through its sense of touch. Among the…

Robotics · Computer Science 2024-04-25 Yuni Fuchioka , Masashi Hamaya

Proprioceptive sensors on planetary rovers serve for state estimation and for understanding terrain and locomotion performance. While inertial measurement units (IMUs) are widely used to this effect, force-torque sensors are less explored…

Robotics · Computer Science 2025-10-31 Levin Gerdes , Carlos Pérez del Pulgar , Raúl Castilla Arquillo , Martin Azkarate

Inspecting large-scale industrial surfaces like aircraft fuselages for quality control requires capturing their precise 3D surface geometry at high resolution. Vision-based tactile sensors (VBTSs) offer high local resolution but require…

Contact-rich manipulation tasks such as precision assembly require precise control of interaction forces, yet existing imitation learning methods rely mainly on vision-only demonstrations. We propose ManipForce, a handheld system designed…

Robotics · Computer Science 2025-09-24 Geonhyup Lee , Yeongjin Lee , Kangmin Kim , Seongju Lee , Sangjun Noh , Seunghyeok Back , Kyoobin Lee

Teleoperation is often limited by the ability of an operator to react and predict the behavior of the robot as it interacts with the environment. For example, to grasp small objects on a table, the teleoperator needs to predict the position…

Robotics · Computer Science 2022-05-17 Guilherme Maeda , Naoki Fukaya , Shin-ichi Maeda
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