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Tactile sensing is an instrumental modality of robotic manipulation, as it provides information that is not accessible via remote sensors such as cameras or lidars. Touch is particularly crucial in unstructured environments, where the robot's internal representation of manipulated objects is uncertain. In this study we present the sensorization of an existing artificial hand, with the aim to achieve fine control of robotic limbs and perception of object's physical properties. Tactile feedback is conveyed by means of a soft sensor integrated at the fingertip of a robotic hand. The sensor consists of an optical fiber, housing Fiber Bragg Gratings (FBGs) transducers, embedded into a soft polymeric material integrated on a rigid hand. Through several tasks involving grasps of different objects in various conditions, the ability of the system to acquire information is assessed. Results show that a classifier based on the sensor outputs of the robotic hand is capable of accurately detecting both size and rigidity of the operated objects (99.36 and 100% accuracy, respectively). Furthermore, the outputs provide evidence of the ability to grab fragile objects without breakage or slippage e and to perform dynamic manipulative tasks, that involve the adaptation of fingers position based on the grasped objects' condition.
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http://dx.doi.org/10.3389/fnbot.2019.00008 | DOI Listing |
ACS Nano
September 2025
International School of Microelectronics, Dongguan University of Technology, Dongguan 523808, China.
Mimicking human brain functionalities with neuromorphic devices represents a pivotal breakthrough in developing bioinspired electronic systems. The human somatosensory system provides critical environmental information and facilitates responses to harmful stimuli, endowing us with good adaptive capabilities. However, current sensing technologies often struggle with insufficient sensitivity, dynamic response, and integration challenges.
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, 510641, China.
Recently, flexible airflow sensors have attracted significant attention due to their impressive characteristics and capabilities for airflow sensing. However, the development of high-performance flexible airflow sensors capable of sensing airflow over large areas remains a challenge. In this work, it is proposed that a hair-like flexible airflow sensor, based on laser direct writing and electrostatic flocking, offers an efficient technology for airflow sensing.
View Article and Find Full Text PDFAdv Mater
September 2025
Key Laboratory of Low Dimensional Quantum Structures and Quantum Control of Ministry of Education, School of Physics and Electronics, Hunan Normal University, Changsha, 410081, China.
The high sensitivity and wide linearity are crucial for flexible tactile sensors in adapting to diverse application scenarios with high accuracy and reliability. However, conventional optimization strategies of constructing microstructures suffer from the mutual restriction between the high sensitivity and wide linearity. Herein, a novel design of localized gradient conductivity (LGC) with partly covered low-conductivity (low-σ) carbon/Polydimethylsiloxane layer on high-conductivity (high-σ) silver nanowires film upon the micro-dome structure is proposed.
View Article and Find Full Text PDFBrain Behav
September 2025
Department of Physical Therapy, Niigata University of Health and Welfare, Niigata, Japan.
Introduction: We aimed to clarify the effects of an active touch intervention using different textures on corticospinal excitability.
Methods: A total of 30 healthy individuals participated in the active touch intervention. Two tactile stimuli were used for intervention: smooth (silk) and rough (hessian) stimuli.
Cell Rep
September 2025
Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA. Electronic address:
The neural circuits that transmit the sense of pain and how pain is encoded by these circuits are still poorly understood.Mechanical allodynia is a prominent form of chronic pain characterized by painful responses to innocuous touch that develops as a consequence of nerve damage and inflammation. Here, we show that alterations to the normal log-normal distribution of neuronal activity and structure of neural correlations between neurons in the dorsal column nuclei (DCN) constitute a signature feature of mechanical allodynia, with the transmission of "allodynic" light touch information to the thalamus by somatostatin-positive projection neurons in the DCN being essential for its expression and development.
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