Search Results (168)

Multidimensional force sensors are key devices capable of simultaneously perceiving and analyzing force in multiple directions (normally triaxial forces). They are designed to provide intelligent systems with skin-like precision in environmental interaction, offering high sensitivity, spatial resolution, decoupling capability, and environmental adaptability. However, the inherent complexity of tactile information coupling, combined with stringent demands for miniaturization, robustness, and low cost in practical applications, makes high-performance and reliable multidimensional sensing and decoupling a major challenge. This drives ongoing innovation in sensor structural design and sensing mechanisms. Various structural strategies have demonstrated significant advantages in improving sensor performance, simplifying decoupling algorithms, and enhancing adaptability—attributes that are essential in scenarios requiring fine physical interactions. From this perspective, this article reviews recent advances in multidimensional force sensing technology, with a focus on the operating principles and performance characteristics of sensors with different structural designs. It also highlights emerging trends toward multimodal sensing and the growing integration with system architectures and artificial intelligence, which together enable higher-level intelligence. These developments support a wide range of applications, including intelligent robotic manipulation, natural human–computer interaction, wearable health monitoring, and precision automation in agriculture and industry. Finally, the article discusses remaining challenges and future opportunities in the development of multidimensional force sensors. Full article

The land used for fruit cultivation now exceeds 120 million hectares globally, with an annual yield of nearly 940 million tons. Fruit picking, the most labor-intensive task in agricultural production, is gradually shifting toward automation using intelligent robotic systems. As the component in direct contact with crops, specialized picking end-effectors perform well for certain fruits but lack adaptability to diverse fruit types and canopy structures. This limitation has constrained technological progress and slowed industrial deployment. The diversity of fruit shapes and the wide variation in damage thresholds—2–4 N for strawberries, 15–40 N for apples, and about 180 N for kiwifruit—further highlight the challenge of universal end-effector design. This review examines two major technical pathways: separation mechanisms and grasping strategies. Research has focused on how fruits are detached and how they can be securely held. Recent advances and limitations in both approaches are systematically analyzed. Most prototypes have achieved picking success rates exceeding 80%, with average cycle times reduced to 4–5 s per fruit. However, most designs remain at Technology Readiness Levels (TRLs) 3–5, with only a few reaching TRLs 6–7 in greenhouse trials. A dedicated section also discusses advanced technologies, including tactile sensing, smart materials, and artificial intelligence, which are driving the next generation of picking end-effectors. Finally, challenges and future trends for highly universal agricultural end-effectors are summarized. Humanoid picking hands represent an important direction for the development of universal picking end-effectors. The insights from this review are expected to accelerate the industrialization and large-scale adoption of robotic picking systems. Full article

Effective environmental monitoring is critical for preventing microbial and allergenic cross-contamination. However, manual swabbing methods, commonly used to verify hygienic conditions, are prone to inconsistent results because of variability in pressure, coverage, and techniques. Two novel solutions will be explored to address these challenges: a robotic swabbing system with tactile sensing control, and a fluorescence/absorbance spectrometer for non-contact, protein-based residue detection. The robotic system was evaluated against trained and untrained humans, measuring water pickup, surface coverage, and pressure consistency. Concurrently, the fluorescence system analyzed model poultry protein soil to correlate spectral patterns with contamination levels. The robotic system demonstrated statistically superior performance, achieving consistent force application and near-complete surface coverage, overcoming key limitations of manual sampling. The fluorescence system distinguished contamination with high sensitivity, validating its use as a rapid, non-contact assessment tool. Together, the robotic sample acquisition and the spectrometer’s sensitive analysis provide a dual-modality framework for enhancing hygiene monitoring in manufacturing facilities. Full article

Despite widespread modular tooling in robots and automated systems, tactile sensing lags behind, constrained by custom and non-interchangeable sensors. To close this gap, we developed a clip-on cylindrical tactile module that combines a snap-fit Clip-on Cap (CC) with a plug-in Sensor Core (PSC) hosting an array of force sensing and temperature-reference fiber Bragg gratings (FBGs). An opto-mechanical model relates Bragg wavelength shifts to external forces through parameterized dimensions and remains applicable across varied module sizes. Two loading configurations are examined: Case I, a PSC fitted with a compliant PSC-solid insert, and Case II, a hollow PSC. Experiments across both configurations validate the model, with prediction errors below 8%. Case II offers up to twice the force sensitivity of Case I, whereas Case I maintains slightly higher linearity (R² > 0.95). We propose a metric, Q, for assessing the trade-off among sensitivity, linearity, and dynamic lag; analyses with this metric establish that softer solid inserts enhance tactile force perception. The CC–PSC pair can be rapidly swapped or detached to meet diverse application needs. These results provide a transferable design and modeling framework for equipping robots—or other automated systems—with universally deployable, clip-on tactile perception. Full article

Polymer gel-based triboelectric nanogenerators (TENGs) have emerged as versatile platforms for self-powered sensing due to their inherent softness, stretchability, and tunable conductivity. This review comprehensively explores the roles of polymer gels in TENG architecture, including their function as triboelectric layers, electrodes, and conductive matrices. We analyze four operational modes—vertical contact-separation, lateral-sliding, single-electrode, and freestanding configurations—alongside key performance metrics. Recent studies have reported output voltages of up to 545 V, short-circuit currents of 48.7 μA, and power densities exceeding 120 mW/m², demonstrating the high efficiency of gel-based TENGs. Gel materials are classified by network structure (single-, double-, and multi-network), matrix composition (hydrogels, aerogels, and ionic gels), and dielectric medium. Strategies to enhance conductivity using ionic salts, conductive polymers, and nanomaterials are discussed in relation to triboelectric output and sensing sensitivity. Morphological features such as surface roughness, porosity, and micro/nano-patterning are examined for their impact on charge generation. Application-focused sections detail the integration of gel-based TENGs in health monitoring (e.g., sweat, glucose, respiratory, and tremor sensing), environmental sensing (e.g., humidity, fire, marine, and gas detection), and tactile interfaces (e.g., e-skin and wearable electronics). Finally, we address current challenges, including mechanical durability, dehydration, and system integration, and outline future directions involving self-healing gels, hybrid architectures, and AI-assisted sensing. This review expands the subject area by synthesizing recent advances and offering a strategic roadmap for developing intelligent, sustainable, and multifunctional TENG-based sensing technologies. Full article

This paper systematically reviews the research progress of underwater soft grasping devices in the field of bionic structure, function integration, and tactile sensing technology by drawing on the structural characteristics of marine organisms such as octopuses, jellyfish, and sea anemones (such as suction cups, umbrella-like muscles, and stinging cells). This paper analyzes the inspiration for the design, the application of innovative materials, and the integration of sensing and driving from marine organisms, including a review of soft robotics technologies, such as shape memory alloys (SMA), ionic polymer metal composite materials (IPMCs), magnetic nanocomposite cilia, etc. The research results emphasize that bionic soft robots have the potential for transformation in completely changing underwater operations by providing enhanced flexibility, efficiency, and environmental adaptability. This work provides a bionic design paradigm and perception-driven integration method for underwater soft operation systems, thereby promoting equipment innovation in the fields of deep-sea exploration and ecological protection. Full article

Building upon recent advances in tactile sensing platforms such as OptoSkin, this research introduces an enhanced multi-touch sensor design that integrates Frustrated Total Internal Reflection (FTIR) technology with embedded Time-of-Flight (ToF) sensors for superior performance. Utilizing a 2 mm thick poly(methyl methacrylate) (PMMA) acrylic light guide with an area of 200 × 300 mm², the system employs the AMS TMF8828 ToF sensor both as the illumination source and the receiver. The selected PMMA, with a refractive index of 1.49, achieves an optical field of view (FoV) of approximately 32 degrees for the ToF receiver and enables signal propagation with minimal optical loss. Remarkably, a single ToF sensor can cover an active area of 195 cm² with a linear resolution of approximately 1 cm and an angular resolution of up to 3.5 degrees. This configuration demonstrates not only the feasibility of direct FTIR–ToF integration without the need for external cameras or electrode arrays but also highlights the potential for precise, scalable, and cost-effective multi-touch sensing over large surfaces. The proposed system offers robust performance even under direct sunlight conditions, setting a new benchmark for advanced tactile interface development across consumer electronics, industrial control, and robotic skin applications. 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

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

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

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