Search Results (464)

Dementia disrupts communication not only as a cognitive process but as a relational practice, leaving people living with dementia (PLwD) at risk of exclusion when language fragments. This study examines how communication closeness, the felt sense of being understood, emotionally attuned, and socially connected, might be supported through Research in and through Design (Ri&tD). Drawing on formative mixed-reality studies and a participatory co-design workshop with PLwD, caregivers, and stakeholders, we iteratively developed a series of playful artifacts culminating in Neighbourly, a tactile board game designed to support relational interaction through rule-based, multimodal play. Across this design genealogy, prototypes were treated as Living Counter-Maps: participatory mappings that made patterns of gesture, rhythm, shared attention, and material engagement visible and discussable. Through iterative interpretation and synthesis, the study identifies three guiding principles for designing for communication closeness: supporting co-regulation rather than correction, enabling multimodal reciprocity, and providing a shared material focus for joint agency. The paper consolidates these insights in the Living Counter-Maps Framework, which integrates counter-mapping and Ri&tD as a methodological approach for studying and designing relational communication in dementia care. Full article

Pedestrian accessibility is a critical dimension of sustainable and inclusive transportation systems, yet many cities lack reliable data on infrastructure features that support visually impaired users. Among these, podotactile paving plays a vital role in guiding movement and ensuring safety at intersections and transit nodes. However, tactile paving networks remain largely absent from digital transport inventories and automated mapping pipelines, limiting the ability of cities to systematically assess accessibility conditions. This paper presents a scalable approach for identifying and mapping podotactile areas from mobile and handheld laser scanning data, broadening the scope of data-driven urban modelling to include infrastructure elements critical for visually impaired pedestrians. The framework is evaluated across multiple sensing modalities and geographic contexts, demonstrating robust generalization to diverse transport environments. Across four dataset configurations from Madrid and Mantova, the proposed DeepLabV3+ model achieved podotactile F1-scores ranging from 0.83 to 0.91, with corresponding IoUs between 0.71 and 0.83. The combined Madrid–Mantova dataset reached an F1-score of 0.86 and an IoU of 0.75, highlighting strong cross-city generalization. By addressing a long-standing gap in transportation accessibility research, this study demonstrates that podotactile paving can be systematically extracted and integrated into transport datasets. The proposed approach supports scalable accessibility auditing, enhances digital transport models, and provides planners with actionable data to advance inclusive and equitable mobility. Full article

The development of human-robot interfaces that support daily social interaction requires biomimetic innovation inspired by the sensory receptors of the five human senses (tactile, olfactory, gustatory, auditory, and visual) and employing soft materials to enable natural multimodal sensing. The receptors have a structure formulated by variegated shapes; therefore, the morphological mimicry of the structure is critical. We proposed a spring-like structure which morphologically mimics the roll-type structure of the Meissner corpuscle, whose haptic performance in various dynamic motions has been demonstrated in another study. This study demonstrated the gustatory performance by using the roll-type Meissner corpuscle. The gustatory iontronic mechanism was analyzed using electrochemical impedance spectroscopy with an inductance-capacitance-resistance meter to determine the equivalent electric circuit and current-voltage characteristics with a potentiostat, in relation to the hydrogen concentration (pH) and the oxidation-reduction potential. In addition, thermo-sensitivity and tactile responses to shearing and contact were evaluated, since gustation on the tongue operates under thermal and concave-convex body conditions. Based on the established properties, the roll-type Meissner corpuscle sensor enables the iontronic behavior to provide versatile multimodal sensitivity among the five senses. The different condition of the application of the electric field in the production of two-types of A and B Meissner corpuscle sensors induces distinctive features, which include tactility for the dynamic motions (for type A) or gustation (for type B). Full article

Highly sensitive bioinspired cutaneous receptors are essential for realistic human-robot interaction. This study presents a biomimetic tactile sensor morphologically modeled after the Meissner corpuscle, designed for high dynamic sensitivity achieved using a coiled configuration. Our proposed electrolytic polymerization technique with magnet-responsive hybrid fluid (HF) was employed to fabricate soft, elastic rubber sensors with embedded coiled electrodes. The coiled configuration, optimized by electrolytic polymerization, exhibited high responsiveness to dynamic motions including pressing, pinching, twisting, bending, and shearing. The mechanism of the haptic property was analyzed by electrochemical impedance spectroscopy (EIS), revealing that reactance variations define an equivalent electric circuit (EEC) whose resistance (R_p), capacitance (C_p), and inductance (L_p) change with applied force; these changes correspond to mechanical deformation and the resulting variation in the sensor’s built-in voltage. The roll-type Meissner-inspired sensor demonstrated fast-adapting behavior and broadband vibratory sensitivity, indicating its potential for high-performance tactile and auditory sensing. These findings confirm the feasibility of electrolytically polymerized hybrid fluid rubber as a platform for next-generation bioinspired haptic interfaces. Full article

We investigate crosstalk effects in a dual-modality tactile–proximity sensing system based on Time-of-Flight (ToF) technology integrated within a flat poly(methyl methacrylate) (PMMA) light guide. Building on the OptoSkin framework, we employ two commercially available TMF8828 multi-zone ToF sensors, one configured for tactile detection via frustrated total internal reflection (FTIR) and the other for external proximity measurements through the same transparent substrate. Controlled experiments were conducted using a 2 cm² silicone pad for tactile interaction and an A4-sized diffuse white target for proximity detection. Additional measurements with a movable PMMA sheet were performed to quantify signal attenuation, peak broadening, and confidence degradation under transparent-substrate conditions. The results demonstrate that the TMF8828 can simultaneously resolve both contact-induced scattering and distant reflections, but that localized interference zones occur when sensor fields of view overlap within the substrate. Histogram analysis reveals the underlying multi-path contributions, providing diagnostic insight not available from black-box ToF devices. These findings highlight both the opportunities and limitations of integrating multiple ToF sensors into transparent waveguides and inform design strategies for scalable robotic skins, wearable interfaces, and multi-modal human–machine interaction systems. Full article

The rapid advancement of flexible electronics has propelled the development of lightweight, wearable piezoresistive sensors that integrate high sensitivity, excellent mechanical properties, and multifunctionality, making them a research hotspot. This work presents a flexible and lightweight multifunctional polyvinyl alcohol (PVA) composite hydrogel film, which is constructed based on a synergistic conductive network of cuttlefish ink-derived carbon nanospheres (CNPs) and polypyrrole (PPy). Within this composite, the CNPs and PPy form an interpenetrating conductive network throughout the PVA matrix, where PPy effectively suppresses the agglomeration of CNPs, thereby significantly enhancing the electron transport efficiency. This unique structure endows the material with improved flame retardancy and hydrophobicity while maintaining its lightweight characteristic. Consequently, the sensor demonstrates fast response (64 ms) and recovery times (66 ms) and a high sensitivity factor of 4.34 kPa⁻¹ within a pressure range of 11.2–16.8 kPa. Excellent stability is retained after nearly 6000 loading–unloading cycles, primarily attributed to the efficient response of the contact points and conductive pathways within the synergistic network under stress. Furthermore, this flexible sensor can not only reliably monitor human physiological activities (such as finger joint bending and facial expression changes) but also generate distinct current responses to subtle mouse-clicking actions, enabling tactile handwriting input. This study provides a novel strategy for constructing high-performance sensing materials by utilizing natural biomass-derived carbon materials and conductive polymers, highlighting the significant application potential of such lightweight, multifunctional hydrogel films in next-generation flexible electronic devices. Full article

Flexible magnetic tactile sensors hold great promise for wearable electronics and intelligent robotics but often suffer from limited strain range and complex magnetic field variations due to rigid-soft coupling between the Hall sensor and magnetic layer. In this study, we propose a Halbach-array-based magnetic tactile sensor that structurally decouples the soft magnetic deformation layer from the rigid Hall sensing unit. The sensor embeds k = 2 Halbach-configured magnetic cubes within a PDMS matrix, while the Hall element is fixed at a remote, rigid location. Numerical analysis using COMSOL Multiphysics demonstrates that the Halbach configuration enhances magnetic field strength and uniformity, achieving mT-level detection even at a distance of 15 mm. Moreover, the Halbach array effectively reduces the field distribution from three-dimensional to one-dimensional, enabling stronger directionality, simplified data processing, and higher sensing frequency. This work establishes a theoretical framework for wide-range, high-precision magnetic tactile sensing through magnetic field tailoring, providing valuable guidance for the design of next-generation flexible sensors for wearable, robotic, and embodied intelligence applications. Full article

Mechanical allodynia is the predominant symptom of neuropathic pain following peripheral nerve injury (PNI) and is characterized by pain evoked by innocuous sensory signals transmitted through low-threshold mechanoreceptive primary afferents, including Aβ fibers. However, the underlying neural mechanisms remain insufficiently understood. Previous studies have suggested that the pathological conversion of tactile input into nociceptive signals involves maladaptive alterations in neural circuits and function within the spinal dorsal horn (SDH). Somatosensory processing and transmission in the SDH are regulated not only by local neuronal circuits but also by descending inputs from the brainstem and higher cortical regions. In this study, we show that chemogenetic silencing of descending neurons projecting directly from the primary somatosensory (S1) cortex to the SDH (S1^→SDH neurons) suppresses both PNI-induced allodynia-like behavior and c-FOS expression in the superficial SDH observed in male rats where touch-sensing Aβ fibers were optogenetically activated. S1^→SDH neurons were excitatory and preferentially targeted excitatory SDH neurons (^S1→SDH neurons) broadly distributed across laminae I–V. ^S1→SDH neurons in the superficial laminae also received excitatory inputs from both Aβ fibers and inhibitory inputs from neuropeptide Y promoter active SDH neurons (NpyP⁺ neurons). Furthermore, loss of inhibition from NpyP⁺ neurons induced Aβ fiber-derived allodynia, which was attenuated by suppressing descending signaling from S1^→SDH neurons to the SDH. Moreover, silencing ^S1→SDH neurons alleviated neuropathic allodynia. These findings identify a new corticospinal mechanism that contributes to Aβ fiber-mediated neuropathic allodynia and highlight the S1→SDH pathway as a potential therapeutic target. Full article

Body size awareness—a component of bodily self-representation—allows animals to match their own dimensions to environmental constraints. This study tested whether reedfish (Erpetoichthys calabaricus), a benthic ray-finned species with limited vision, can evaluate aperture passability relative to their body size. Eight fish performed a “body-as-obstacle” task. After training, each individual completed 36 trials in Experiment 1 (three passable circular apertures of different diameters) and 72 trials in Experiment 2 (one small passable and two larger non-passable apertures). We scored first approach, first penetration attempt, and full passage; data were analyzed with generalized linear models. In Experiment 1, choices were random, unaffected by aperture size or position. In Experiment 2, first approaches were random, but first penetration attempts—and ensuing passages—were directed almost exclusively to the single passable aperture. These results indicate near-field formation of pass/not-pass judgments, likely via tactile and hydrodynamic sensing. The behavioral dissociation between exploratory (epistemic) and goal-directed (pragmatic) actions supports a modular model of self-representation, where distinct sensorimotor loops underlie information gathering and goal execution. Thus, reedfish demonstrate body-size awareness and contribute to comparative evidence that modular self-representation and embodied anticipation may extend deep into vertebrate evolution. Full article

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