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Tactile sensing is a essential for skilled manipulation and object perception, but existing devices are unable to capture mechanical signals in the full gamut of regimes that are important for human touch sensing, and are unable to emulate…

Robotics · Computer Science 2019-08-23 Yitian Shao , Hui Hu , Yon Visell

Most modern smartphones are equipped with a barometer to sample air pressure. Accessing these samples is deemed harmless, hence does not require any permission. In this work, we show, however, that these samples can reveal sensitive…

Cryptography and Security · Computer Science 2020-08-11 Alireza Hafez , Dorsa Nahid , Majid Khabbazian

Tactile sensing for robotics is achieved through a variety of mechanisms, including magnetic, optical-tactile, and conductive fluid. Currently, the fluid-based sensors have struck the right balance of anthropomorphic sizes and shapes and…

Research on tactile sensing has been progressing at constant pace. In robotics, tactile sensing is typically studied in the context of object grasping and manipulation. In this domain, the development of robust, multi-modal, tactile sensors…

Robotics · Computer Science 2022-06-29 Lorenzo Natale , Giorgio Cannata

Whole body tactile perception via tactile skins offers large benefits for robots in unstructured environments. To fully realize this benefit, tactile systems must support real-time data acquisition over a massive number of tactile sensor…

Robotics · Computer Science 2016-03-07 Brayden Hollis , Stacy Patterson , Jeff Trinkle

Mobile devices' user interfaces are still quite similar to traditional interfaces offered by desktop computers, but those can be highly problematic when used in a mobile context. Human gesture recognition in mobile interaction appears as an…

Human-Computer Interaction · Computer Science 2014-02-07 Ricardo João Silveira Santos Gamboa

Learning from demonstration is a proven technique to teach robots new skills. Data quality and quantity play a critical role in the performance of models trained using data collected from human demonstrations. In this paper we enhance an…

Robotics · Computer Science 2024-04-02 Catie Cuan , Allison Okamura , Mohi Khansari

We introduce a novel multimodal mobile database called HuMIdb (Human Mobile Interaction database) that comprises 14 mobile sensors acquired from 600 users. The heterogeneous flow of data generated during the interaction with the smartphones…

Human-Computer Interaction · Computer Science 2020-06-01 Alejandro Acien , Aythami Morales , Julian Fierrez , Ruben Vera-Rodriguez , Ivan Bartolome

Imitation learning for robot dexterous manipulation, especially with a real robot setup, typically requires a large number of demonstrations. In this paper, we present a data-efficient learning from demonstration framework which exploits…

This work builds on the previous introduction [1] of a coupled experimental-computational system devised to fully characterize the thermal behavior of complex 3D submicron electronic devices. The new system replaces the laser-based surface…

Materials Science · Physics 2007-09-13 Peter E. Raad , Pavel L. Komarov , M. Burzo

Traditional methods for achieving high localization accuracy on tactile sensors usually involve a matrix of miniaturized individual sensors distributed on the area of interest. This approach usually comes at a price of increased complexity…

In this communication, we present a high resolution tactile plate that can localize one or two contact fingers. The localization principle is based on Lamb wave absorption. Fingers' contact will generate absorption signals while Lamb waves…

Classical Physics · Physics 2009-09-21 Yuan Liu , Jean-Pierre Nikolovski , Moustapha Hafez , Nazih Mechbal , Michel Vergé

Today's tactile sensors have a variety of different designs, making it challenging to develop general-purpose methods for processing touch signals. In this paper, we learn a unified representation that captures the shared information…

Soft sensors that can discriminate shear and normal force could help provide machines the fine control desirable for safe and effective physical interactions with people. A capacitive sensor is made for this purpose, composed of patterned…

Tactile sensing is critical to fine-grained, contact-rich manipulation tasks, such as insertion and assembly. Prior research has shown the possibility of learning tactile-guided policy from teleoperated demonstration data. However, to…

Robotics · Computer Science 2025-02-07 Kelin Yu , Yunhai Han , Qixian Wang , Vaibhav Saxena , Danfei Xu , Ye Zhao

Camera-based tactile sensors are emerging as a promising inexpensive solution for tactile-enhanced manipulation tasks. A recently introduced FingerVision sensor was shown capable of generating reliable signals for force estimation, object…

With the advent of smartphones, there has been a recent increase in the use of capacitive touch sensing for various Human Machine Interfaces (HMI). Capacitive-based touch sensing provides higher flexibility and cost-effectiveness than,…

Emerging Technologies · Computer Science 2024-12-11 Subramaniam Saravana Sankar , Stanislav Kovar , Martin Pospisilik , Michael Galda

Robots which interact with the physical world will benefit from a fine-grained tactile understanding of objects and surfaces. Additionally, for certain tasks, robots may need to know the haptic properties of an object before touching it. To…

Robotics · Computer Science 2016-04-13 Yang Gao , Lisa Anne Hendricks , Katherine J. Kuchenbecker , Trevor Darrell

Since wearable technology was first conceptualized in 1960, it has become a crucial aspect of our daily life. People's daily lives have been made better and their health and well-being have improved because of its convenience, real-time,…

Human-Computer Interaction · Computer Science 2023-11-17 Li He

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