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In this paper, we present a method to manipulate unknown objects in-hand using tactile sensing without relying on a known object model. In many cases, vision-only approaches may not be feasible; for example, due to occlusion in cluttered…

Robotics · Computer Science 2023-03-14 Chaoyi Pan , Marion Lepert , Shenli Yuan , Rika Antonova , Jeannette Bohg

Tactile perception using vibration sensation helps robots recognize their environment's physical properties and perform complex tasks. A sliding motion is applied to target objects to generate tactile vibration data. However, situations…

Robotics · Computer Science 2021-04-21 Naoto Komeno , Takamitsu Matsubara

We aimed to develop a tactile display that allows users to actively explore the virtual texture of a surface. We developed a tactile display embedded in an optical mouse that provides a wide range of frequency vibrations to the user's…

Human-Computer Interaction · Computer Science 2024-11-11 Asahi Kurokawa , Masaharu Shimizu , Mitsuhito Ando , Haruo Noma

This paper addresses the problem of simultaneously exploring an unknown object to model its shape, using tactile sensors on robotic fingers, while also improving finger placement to optimise grasp stability. In many situations, a robot will…

Robotics · Computer Science 2021-07-20 Cristiana de Farias , Naresh Marturi , Rustam Stolkin , Yasemin Bekiroglu

Recent advances in the field of intelligent robotic manipulation pursue providing robotic hands with touch sensitivity. Haptic perception encompasses the sensing modalities encountered in the sense of touch (e.g., tactile and kinesthetic…

We study the problem of using high-resolution tactile sensors to control the insertion of objects in a box-packing scenario. We propose a new system based on a tactile sensor GelSlim for the dense packing task. In this paper, we propose an…

Robotics · Computer Science 2019-09-13 Siyuan Dong , Alberto Rodriguez

Humans rely on touch and tactile sensing for a lot of dexterous manipulation tasks. Our tactile sensing provides us with a lot of information regarding contact formations as well as geometric information about objects during any…

Robotics · Computer Science 2023-06-06 Kei Ota , Devesh K. Jha , Hsiao-Yu Tung , Joshua B. Tenenbaum

This paper presents a novel framework for integration of vision and tactile sensing by localizing tactile readings in a visual object map. Intuitively, there are some correspondences, e.g., prominent features, between visual and tactile…

Robotics · Computer Science 2017-08-16 Shan Luo , Wenxuan Mou , Kaspar Althoefer , Hongbin Liu

Optical tactile sensors are extensively utilized in intelligent robot manipulation due to their ability to acquire high-resolution tactile information at a lower cost. However, achieving adequate reality and versatility in simulating…

Robotics · Computer Science 2024-05-07 Zirong Shen , Yuhao Sun , Shixin Zhang , Zixi Chen , Heyi Sun , Fuchun Sun , Bin Fang

Tactile sensing is crucial in robotics and wearable devices for safe perception and interaction with the environment. Optical tactile sensors have emerged as promising solutions, as they are immune to electromagnetic interference and have…

Traditional methods to achieve high localization accuracy with tactile sensors usually use a matrix of miniaturized individual sensors distributed on the area of interest. This approach usually comes at a price of increased complexity in…

We develop a real-time state estimation system to recover the pose and contact formation of an object relative to its environment. In this paper, we focus on the application of inserting an object picked by a suction cup into a tight space,…

Robotics · Computer Science 2018-03-22 Kuan-Ting Yu , Alberto Rodriguez

We present an active tactile exploration framework for joint object recognition and 6D pose estimation. The proposed method integrates wrist force/torque sensing, GelSight tactile sensing, and free-space constraints within a Bayesian…

Tactile exploration plays a crucial role in understanding object structures for fundamental robotics tasks such as grasping and manipulation. However, efficiently exploring such objects using tactile sensors is challenging, primarily due to…

This paper explores active sensing strategies that employ vision-based tactile sensors for robotic perception and classification of fabric textures. We formalize the active sampling problem in the context of tactile fabric recognition and…

Knowledge of 3-D object shape is of great importance to robot manipulation tasks, but may not be readily available in unstructured environments. While vision is often occluded during robot-object interaction, high-resolution tactile sensors…

Robotics · Computer Science 2022-03-11 Sudharshan Suresh , Zilin Si , Joshua G. Mangelson , Wenzhen Yuan , Michael Kaess

Object surface reconstruction brings essential benefits to robot grasping, object recognition, and object manipulation. When measuring the surface distribution of an unknown object by tapping, the greatest challenge is to select tapping…

Robotics · Computer Science 2021-10-20 Su Sun , Byung-Cheol Min

Efficient and accurate 3D object shape reconstruction contributes significantly to the success of a robot's physical interaction with its environment. Acquiring accurate shape information about unknown objects is challenging, especially in…

Robotics · Computer Science 2023-08-02 Yiting Chen , Ahmet Ercan Tekden , Marc Peter Deisenroth , Yasemin Bekiroglu

Tactile sensing has recently been used in robotics for object identification, grasping, and material recognition. Most material recognition approaches use vibration information from a tactile exploration, typically above one second long, to…

Robotics · Computer Science 2023-11-08 Augusto Gómez Eguíluz , Ignacio Rañó , Sonya A. Coleman , T. Martin McGinnity

Inspired by the human ability to perform complex manipulation in the complete absence of vision (like retrieving an object from a pocket), the robotic manipulation field is motivated to develop new methods for tactile-based object…

Robotics · Computer Science 2022-07-22 Jingxi Xu , Shuran Song , Matei Ciocarlie
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