Search Results (455)

Soft robotic grippers have emerged as crucial tools for safe and adaptive manipulation of delicate and different objects, enabled by their compliant structures. These grippers need embedded sensing that offers proprioceptive and exteroceptive feedback in order to function consistently. Resistive sensing is unique among transduction processes since it is easy to use, scalable, and compatible with deformable materials. The three main classes of resistive sensors used in soft robotic grippers are systematically examined in this review: ionic sensors, which are emerging multimodal devices that can capture both mechanical and environmental cues; tactile sensors, which detect contact, pressure distribution, and slip; and strain sensors, which monitor deformation and actuation states. Their methods of operation, material systems, fabrication techniques, performance metrics, and integration plans are all compared in the survey. The results show that sensitivity, linearity, durability, and scalability are all trade-offs across sensor categories, with ionic sensors showing promise as a new development for multipurpose soft grippers. There is also a discussion of difficulties, including hysteresis, long-term stability, and signal processing complexity. In order to move resistive sensing from lab prototypes to reliable, practical applications in domains like healthcare, food handling, and human–robot collaboration, the review concludes that developments in hybrid material systems, additive manufacturing, and AI-enhanced signal interpretation will be crucial. Full article

Autonomous navigation in GPS-denied, unstructured environments such as murky waters or complex seabeds remains a formidable challenge for robotic systems, primarily due to sensory degradation and the computational inefficiency of conventional algorithms. Drawing inspiration from the robust navigation strategies of marine species such as the sea turtle’s quantum-assisted magnetoreception, the octopus’s tactile-chemotactic integration, and the jellyfish’s energy-efficient flow sensing this study introduces a novel neuromorphic framework for resilient robotic navigation, fundamentally based on the co-design of marine-inspired sensors and event-based neuromorphic processors. Current systems lack the dynamic, context-aware multisensory fusion observed in these animals, leading to heightened susceptibility to sensor failures and environmental perturbations, as well as high power consumption. This work directly bridges this gap. Our primary contribution is a hybrid sensor fusion model that co-designs advanced sensing replicating the distributed neural processing of cephalopods and the quantum coherence mechanisms of migratory marine fauna with a neuromorphic processing backbone. Enabling real-time, energy-efficient path integration and cognitive mapping without reliance on traditional methods. This proposed framework has the potential to significantly enhance navigational robustness by overcoming the limitations of state-of-the-art solutions. The findings suggest the potential of marine bio-inspired design for advancing autonomous systems in critical applications such as deep-sea exploration, environmental monitoring, and underwater infrastructure inspection. Full article

We evaluate tactile-first robotic traversal on the Department of Homeland Security (DHS) figure-8 mobility test using a two-way repeated-measures design across various algorithms (three tactile policies—M1 reactive, M2 terrain-weighted, M3 memory-augmented; a monocular camera baseline, CB-V; a tactile histogram baseline, T-VFH; and an optional tactile-informed replanner, T-D* Lite) and lighting conditions (Indoor, Outdoor, and Dark). The platform is the custom-built Eleven robot—a quadruped integrating a joint-mounted tactile tentacle with a tip force-sensitive resistor (FSR; Walfront 9snmyvxw25, China; 0–10 kg range, ≈0.1 N resolution @ 83 Hz) and a woven Galvorn carbon-nanotube (CNT) yarn for proprioceptive bend sensing. Control and sensing are fully wireless via an ESP32-S3, Arduino Nano 33 BLE, Raspberry Pi 400, and a mini VESC controller. Across 660 trials, the tactile stack maintained ∼21 ms (p50) policy latency and mid-80% success across all lighting conditions, including total darkness. The memory-augmented tactile policy (M3) exhibited consistent robustness relative to the camera baseline (CB-V), trailing by only ≈3–4% in Indoor and ≈13–16% in Outdoor and Dark conditions. Pre-specified, two one-sided tests (TOSTs) confirmed no speed equivalence in any M3↔CB-V comparison. Unlike vision-based approaches, tactile-first traversal is invariant to illumination and texture—an essential capability for navigation in darkness, smoke, or texture-poor, confined environments. Overall, these results show that a tactile-first, memory-augmented control stack achieves lighting-independent traversal on DHS benchmarks while maintaining competitive latency and success, trading modest speed for robustness and sensing independence. Full article

Simultaneous measurement of force and position often relies on delicate tactile sensing systems that only measure small forces at discrete positions. This study proposes a compact, durable sensor which can provide simultaneous and continuous measurements of force and position using multiple strain gauges mounted on a cantilever beam. When a point force is applied to the cantilever, the strain gauges are used to determine the magnitude of the applied force and its position along the beam. A major advantage of the force-position sensor concept is its compact electronics and durable sensing surface. We designed, tested, and evaluated three different prototypes for the force-position sensor concept. The prototypes achieved an average percent error of 1.71% and were highly linear. We also conducted a thorough analysis of design variables and their effects on performance. The force and position measurement ranges can be adjusted by tuning the material and geometric properties of the beam and the spacing of the strain gauges. The accuracy of force measurements is dependent upon applied load, but insensitive to the location of the applied load. Accuracy of position measurements is also dependent upon applied load and weakly dependent upon position of the applied load. Full article

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

Virtual communication, involving the transmission of all human senses, is the next step in the development of telecommunications. Achieving this vision requires real-time data exchange with low latency, which in turn necessitates the implementation of the Tactile Internet (TI). TI will ensure the transmission of high-quality tactile data, especially when combined with audio and video signals, thus enabling more realistic interactions in virtual environments. In this context, advances in realism increasingly depend on the accurate simulation of the grasping process and hand–object interactions. To address this, in this paper, we methodically present the challenges of human–object interaction in virtual environments, together with a detailed review of the datasets used in grasping modeling and the integration of physics-based and machine learning approaches. Based on this review, we propose a multi-step framework that simulates grasping as a series of biomechanical, perceptual, and control processes. The proposed model aims to support realistic human interaction with virtual objects in immersive settings and to enable integration into applications such as remote manipulation, rehabilitation, and virtual learning. Full article

With the rapid development of wearable devices and intelligent human–machine interaction technologies, the demand for high-precision pressure sensors has soared. Piezoresistive pressure sensors excel due to their simple structure, low cost, and high sensitivity, among which flexible piezoresistive pressure sensors based on porous polymers have become a research focus, thanks to their unique 3D porous structure and excellent performance. This review summarizes recent advances: it introduces key performance metrics and the piezoresistive sensing mechanism; outlines porous structure preparation methods (phase separation, 3D printing, electrospinning) with their principles, advantages, and limitations; examines conductive fillers (carbon-based, polymer, metal, MXene) with their properties and applications; and highlights flexible substrates (silicone, polyurethane, polyimide, natural polymers) in ensuring mechanical compliance and device integration. Studies show material innovation, structural optimization, and process improvement can significantly enhance sensor accuracy, stability, and durability, helping break traditional performance bottlenecks. Future prospects are broad in tactile sensing, biomedical monitoring, and human–machine interaction, providing references for related research and industrial development. 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

A novel endoscopic palpation tool (EPT), designed for tactile and stiffness sensing using fiber Bragg gratings (FBGs) was evaluated in a surgical environment for intraoperative safety and effectiveness. The EPT consisted of four FBGs arranged in a cross pattern and embedded within an elastic, hollow, silicone hemispherical dome designed to deform upon contact with soft tissue. The EPT was employed to scan both in vivo and ex vivo tissue samples. Monitoring of porcine vital signs during minimally invasive and open surgical procedures showed no significant changes during use of the EPT. Perioperative blood tests including inflammatory markers and liver and renal function studies were unremarkable. Histopathological analyses of tissues involved (liver, spleen, bowel, and abdominal wall) showed no evidence of inflammation, necrosis, or tissue damage, confirming the device’s biocompatibility. To the best of our knowledge, this is the first study reporting in vivo stiffness measurements using an FBG-based EPT. The probe successfully distinguished between soft and hard tissue regions’ relative stiffness. Furthermore, successive measurements on liver samples demonstrated the device’s ability to generate stiffness maps, enabling clear visualization of spatial variation in tissue stiffness. 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

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