Search Results (441)

Flexible pressure sensors have shown promise applications in scenarios such as robotic tactile sensing due to their excellent sensitivity and linearity. However, the realization of flexible pressure sensors with both static and dynamic response capabilities still face significant challenges due to the properties of the sensing materials themselves. In this study, we propose a flexible pressure sensor that integrates piezoelectric and ionic capacitance mechanisms for full-domain response detection of dynamic and static forces: a “sandwich” sensing structure is constructed by printing a mixture of multi-walled carbon nanotubes (MWCNTs) onto the surface of the upper and lower electrodes, and sandwiching a polyvinylidene fluoride (PVDF) thin film between the electrodes. The device exhibits a sensitivity of 0.13 kPa⁻¹ in the pressure range of 0–150 kPa. The sensor has a rapid dynamic response (response time 19 ms/12 ms) with a sensitivity of 0.49 mV kPa⁻¹ based on the piezoelectric mechanism and a linearity of 0.9981 based on the ionic capacitance mechanism. The device maintains good response stability under the ball impact test, further validating its potential application in static/dynamic composite force monitoring scenarios. Full article

This study presents a novel, fully passive radiofrequency (RF)-based localization system designed to detect the position of a robotic hand on a flat surface within its tactile range, particularly in scenarios where other sensing systems may face limitations. The system employs U-shaped, chipless resonator tags printed on the surface using a customized conductive ink, together with a coplanar RF probe integrated into the robotic hand, to determine position through impedance variations. Unlike conventional approaches, the proposed method provides a compact, low-cost, and robust solution that is resilient to variations in lighting, dust, and other environmental conditions. The resonator tags are arranged in a structured grid inspired by a Sudoku pattern, enabling both position and orientation detection in the near-field region. The system is fabricated on 3D-printed flexible substrates using a flexible and stretchable conductive ink, and its performance is validated through both electromagnetic simulations and experimental measurements. The results confirm that the proposed approach enables accurate and repeatable two-dimensional localization of the robotic hand under various configurations. This work introduces a scalable, high-precision, and vision-independent sensing platform with strong potential for robotic manipulation in challenging environments. Full article

With the maturity of haptic technology and complex systems, tactile interaction has gradually become realized through specific hardware and software configurations in the e-commerce and business industries. As an innovative form depending on haptic systems, tactile interactive advertising could help both advertisers and consumers enhance the haptic experience of products through technology-mediated virtual environments and provide tactile information for purchase decision making that relies on restoring the real sense of touch. On the basis of the value-based adoption model (VAM) and the need for touch (NFT) from a preference for haptic information in a system, we conduct quantitative research and construct a partial least squares structural equation model, which aims to study the influencing factors that characterize the user preference of tactile interactive advertisements empowered by haptic systems among Chinese consumers. A total of 509 valid questionnaires were collected through online and offline channels. The study revealed that the perceived enjoyment (PE) and telepresence (TEL) of tactile interactive advertisements as benefit factors positively influence the perceived value (PV) and that the perceived fee (PF) as a sacrifice factor negatively influences PV, which further impacts the attitude and intention to use (IU). In addition, the study verified that a higher NFT positively affected PE, PU, and PF and IU for the perception of tactile interactive advertising. Through this study, we aim to provide insights from a consumer perspective to enhance the advertising effect and user experience through tactile interaction in further e-commerce, which transforms how we interact with digital systems and virtual environments. Full article

Rapid developments in intelligent interfaces across service, healthcare, and industry have led to unprecedented demands for advanced tactile perception systems. Traditional tactile sensors often struggle with adaptability on curved surfaces and lack sufficient feedback for delicate interactions. Flexible and wearable tactile sensors are emerging as a revolutionary solution, driven by innovations in flexible electronics and micro-engineered materials. This paper reviews recent advancements in flexible tactile sensors, focusing on their mechanisms, multifunctional performance and applications in health monitoring, human–machine interactions, and robotics. The first section outlines the primary transduction mechanisms of piezoresistive (resistance changes), capacitive (capacitance changes), piezoelectric (piezoelectric effect), and triboelectric (contact electrification) sensors while examining material selection strategies for performance optimization. Next, we explore the structural design of multifunctional flexible tactile sensors and highlight potential applications in motion detection and wearable systems. Finally, a detailed discussion covers specific applications of these sensors in health monitoring, human–machine interactions, and robotics. This review examines their promising prospects across various fields, including medical care, virtual reality, precision agriculture, and ocean monitoring. Full article

Much as the information generated by our fingertips is used for fine-scale grasping and manipulation, closed-loop dexterous robotic manipulation requires rich tactile information to be generated by artificial fingertip sensors. In particular, fingertip shear sensing dominates modalities such as twisting, dragging, and slipping, but there is limited research exploring soft shear predictions from an increasingly popular single-material tactile technology: electrical impedance tomography (EIT). Here, we focus on the twisting of a screwdriver as a representative shear-based task in which the signals generated by EIT hardware can be analyzed. Since EIT’s analytical reconstructions are based upon conductivity distributions, we propose and investigate five reduced-order models which relate shear-based screwdriver twisting to the conductivity maps of a robot’s single-material sensorized fingertips. We show how the physical basis of our reduced-order approach means that insights can be deduced from noisy signals during the twisting tasks, with respective torque and diameter correlations of 0.96 and 0.97 to our reduced-order parameters. Additionally, unlike traditional reconstruction techniques, all necessary FEM model signals can be precalculated with our approach, promising a route towards future high-speed closed-loop implementations. Full article

High-density tactile sensor arrays that replicate human touch could restore texture perception in paralyzed individuals. However, conventional tactile sensor arrays face inherent trade-offs between spatial resolution, sensitivity, and crosstalk suppression due to microstructure size limitations and signal interference. To address this, we developed a tactile sensor featuring 10 μm-scale pyramid tips that achieve ultra-high sensitivity (8.082 kPa⁻¹ in 0.2–0.5 kPa range). By integrating a flexible resistive sensing layer with a 256 × 256 active-matrix thin-film transistor (TFT) readout system, our design achieves 500 μm spatial resolution—surpassing human fingertip discrimination thresholds. The sensor demonstrates rapid response (125 ms), exceptional stability (>1000 cycles), and successful reconstruction of 500 μm textures and Braille patterns. This work establishes a scalable platform for high-fidelity tactile perception in static fine texture recognition. Full article

Ungual disorders can impact quality of life, with onychomycosis and nail psoriasis being the most prevalent disorders among the general population. In humans, the main functions of the nail apparatus comprise protection against trauma, improvement of tactile sensations, and allowing precision gripping. In order to perform such functions, the nail plate has a hard structure formed by dead keratinized corneocytes tightly bound to each other, giving the nail plate a “barrier-like” character. Due to this property of the nail plate, drug delivery to the region is hindered, making the treatment of ungual disorders difficult, either by systemic or topical drug administration. Many strategies have been developed in the last few decades in an attempt to increase the bioavailability of drugs in the nail. Interest in the employment of nanostructured drug delivery systems aiming to increase the bioavailability of drugs in the nail plate upon topical administration has increased. Moreover, the association of the nanotechnological approaches with other methods may be a beneficial strategy when aiming to increase drug permeation through the nail barrier. In this sense, the present review has the intention of presenting the panorama of the current technological development of nanostructured systems designed for the local treatment of ungual disorders. Through this extensive literature review, it was possible to recognize, among the studies, a lack of standardization regarding the methodology of nail permeation assessment, which imposes an obstacle to comparison. Full article

Tactile sensing is increasingly vital in robotics, especially for tasks like object manipulation and texture classification. Among tactile technologies, optical and electrical sensors are widely used, yet no rigorous direct comparison of their performance has been conducted. This paper addresses that gap by presenting a comparative study between a high-resolution optical tactile sensor (a modified TacTip) and a low-resolution electrical sensor combining accelerometers and piezoelectric elements. We evaluate both sensor types on two tasks: texture classification and coefficient of dynamic friction prediction. Various configurations and resolutions were explored, along with multiple machine learning classifiers to determine optimal performance. The optical sensor achieved 99.9% accuracy on a challenging texture dataset, significantly outperforming the electrical sensor, which reached 82%. However, for dynamic friction prediction, both sensors performed comparably, with only a $\tilde{5}$% accuracy difference. We also found that the optical sensor retained high classification accuracy even when image resolution was reduced to 25% of its original size, suggesting that ultra-high resolution is not essential. In conclusion, the optical sensor is the better choice when high accuracy is required. However, for low-cost or computationally efficient systems, the electrical sensor provides a practical alternative with competitive performance in some tasks. Full article

In this research paper, we have implemented a computer program thanks to the XML language to sense the differences in image color depth by using haptic/tactile devices. With the use of “Bump Map” and tools such as “Autodesk’s 3D Studio Max”, “Adobe Photoshop”, and “Adobe Illustrator”, we were able to obtain the desired results. The haptic devices used for the experiments were the “PHANTOM Touch” and the “PHANTOM Omni R” of “3D Systems”. The programs that were installed and configured properly so as to model the surfaces, run the experiments, and finally achieve the desired goal are “H3D Api”, “Geomagic_OpenHaptics”, and “OpenHaptics_Developer_Edition”. The purpose of this project was to feel different textures, shapes, and objects in images by using a haptic device. The primary objective was to create a system from the ground up to render visuals on the screen and facilitate interaction with them via the haptic device. The main focus of this work is to propose a novel pattern of images that we can classify as different textures so that they can be identified by people with reduced vision. Full article

Robotic assembly of electrical connectors enables the automation of high-efficiency production of electronic products. A rigid gripper is adopted as the end-effector by the majority of existing works with a force–torque sensor installed at the wrist, which suffers from very limited perception capability of the manipulated objects. Moreover, the grasping and movement actions, as well as the inconsistency between the robot base and the end-effector frame, tend to result in angular misalignment, usually leading to assembly failure. Bio-inspired by the human finger, we designed a tactile finger in this paper with three characteristics: (1) Compliance: A soft ‘skin’ layer provides passive compliance for plenty of manipulation actions, thus increasing the tolerance for alignment errors. (2) Tactile Perception: Two types of sensing elements are embedded into the soft skin to tactilely sense the involved contact status. (3) Enhanced manipulation force: A rigid fingernail is designed to enhance the manipulation force and enable potential delicate operations. Moreover, a tactile-based alignment algorithm is proposed to search for the optimal orientation angle about the z axis. In the application of U-disk insertion, the three characteristics are validated and a success rate of 100% is achieved, whose generalization capability is also validated through the assembly of three types of electrical connectors. Full article

Sign language recognition plays a crucial role in enabling communication for deaf individuals, yet current methods face limitations such as sensitivity to lighting conditions, occlusions, and lack of adaptability in diverse environments. This study presents a wearable multi-channel tactile sensing system based on smart textiles, designed to capture subtle wrist and finger motions for static sign language recognition. The system leverages triboelectric yarns sewn into gloves and sleeves to construct a skin-conformal tactile sensor array, capable of detecting biomechanical interactions through contact and deformation. Unlike vision-based approaches, the proposed sensor platform operates independently of environmental lighting or occlusions, offering reliable performance in diverse conditions. Experimental validation on American Sign Language letter gestures demonstrates that the proposed system achieves high signal clarity after customized filtering, leading to a classification accuracy of 94.66%. Experimental results show effective recognition of complex gestures, highlighting the system’s potential for broader applications in human-computer interaction. Full article

In this paper, we propose an active touch sensing algorithm designed for robust hole localization in 3D objects, specifically aimed at assembly tasks such as peg-in-hole operations. Unlike general object detection algorithms, our solution is tailored for precise localization of features like hole openings using sparse tactile feedback. The method builds on a prior 3D map of the object and employs a series of iterative search algorithms to refine localization by aligning tactile sensing data with the object’s shape. It is specifically designed for objects composed of multiple parallel surfaces located at distinct heights; a common characteristic in many assembly tasks. In addition to the deterministic approach, we introduce a probabilistic version of the algorithm, which effectively compensates for sensor noise and inaccuracies in the 3D map. This probabilistic framework significantly improves the algorithm’s resilience in real-world environments, ensuring reliable performance even under imperfect conditions. We validate the method’s effectiveness for several assembly tasks, such as inserting a plug into a socket, demonstrating its speed and accuracy. The proposed algorithm outperforms traditional search strategies, offering a robust solution for assembly operations in industrial and domestic applications with limited sensory input. Full article

Sophisticated energy-harvesting technologies have swiftly progressed, expanding energy supply distribution and leveraging advancements in self-sustaining electronic devices. Despite substantial advancements in friction nanomotors within the last decade, a considerable technical obstacle remains for their flawless incorporation using printed electronics and autonomous devices. Integrating advanced triboelectric nanogenerator (TENG) technology with the rapidly evolving field of composite material 3D printing with has resulted in the advancement of three-dimensionally printed TENGs. Triboelectric nanogenerators are an important part of the next generation of portable energy harvesting and sensing devices that may be used for energy harvesting and artificial intelligence tasks. This paper systematically analyzes the continual development of 3D-printed TENGs and the integration of composite materials. The authors thoroughly review the latest material combinations of composite materials and 3D printing techniques for TENGs. Furthermore, this paper showcases the latest applications, such as using a TENG device to generate energy for electrical devices and harvesting energy from human motions, tactile sensors, and self-sustaining sensing gloves. This paper discusses the obstacles in constructing composite-material-based 3D-printed TENGs and the concerns linked to research and methods for improving electrical output performance. The paper finishes with an assessment of the issues associated with the evolution of 3D-printed TENGs, along with innovations and potential future directions in the dynamic realm of composite-material-based 3D-printed TENGs. Full article

Blindness and low vision are increasing serious public health issues that affect a significant percentage of the population worldwide. Vision plays a crucial role in spatial navigation and daily activities. Its reduction or loss creates numerous challenges for an individual. Assistive technology can enhance mobility and navigation in outdoor environments. In the field of orientation and mobility training, technologies with haptic interaction can assist individuals with visual impairments in learning how to navigate safely and effectively using the sense of touch. This paper presents a virtual reality platform designed to support the development of navigation techniques within a safe yet realistic environment, expanding upon existing research in the field. Following extensive optimization, we present a visual representation that accurately simulates various 3D tile textures using graphics replicating real tactile surfaces. We conducted a user interaction study in a virtual environment consisting of 3D navigation tiles enhanced with tactile textures, placed appropriately for a real-world scenario, to assess user performance and experience. This study also assess the usability and user experience of the platform. We hope that the findings will contribute to the development of new universal navigation techniques for people with visual impairments. Full article

Optical tactile sensing is gaining traction as a foundational technology in collaborative and human-interactive robotics, where reliable touch and pressure feedback are critical. Traditional systems based on total internal reflection (TIR) and frustrated TIR (FTIR) often require complex infrared setups and lack adaptability to curved or flexible surfaces. To overcome these limitations, we developed OptoSkin—a novel tactile platform leveraging direct time-of-flight (ToF) LiDAR principles for robust contact and pressure detection. In this extended study, we systematically evaluate how key optical properties of waveguide materials affect ToF signal behavior and sensing fidelity. We examine a diverse set of materials, characterized by varying light transmission (82–92)%, scattering coefficients (0.02–1.1) cm⁻¹, diffuse reflectance (0.17–7.40)%, and refractive indices 1.398–1.537 at the ToF emitter wavelength of 940 nm. Through systematic evaluation, we demonstrate that controlled light scattering within the material significantly enhances ToF signal quality for both direct touch and near-proximity sensing. These findings underscore the critical role of material selection in designing efficient, low-cost, and geometry-independent optical tactile systems. Full article