Biomimetic Tactile Sensors with Bilayer Fingerprint Ridges Demonstrating Texture Recognition

Recent Developments and Applications of Tactile Sensors with Biomimetic Microstructures

Humans possess an innate ability to perceive a wide range of objects through touch, which allows them to interact effectively with their surroundings. Similarly, tactile perception in artificial sensory systems enables the acquisition of object properties, human physiological signals, and environmental information. Biomimetic tactile sensors, as an emerging sensing technology, draw inspiration from biological systems and exhibit high sensitivity, rapid response, multimodal perception, and stability. By mimicking biological mechanisms and microstructures, these sensors achieve precise detection of mechanical signals, thereby paving the way for advancements in tactile sensing applications. This review provides an overview of key sensing mechanisms, microstructure designs, and advanced fabrication techniques of biomimetic tactile sensors. The system architecture design of biomimetic tactile sensing systems is also explored. Furthermore, the review highlights significant applications of these sensors in recent years, including texture recognition, human health detection, and human-machine interaction. Finally, the key challenges and future development prospects related to biomimetic tactile sensors are discussed.

Transforming Object Design and Creation: Biomaterials and Contemporary Manufacturing Leading the Way

In the field of three-dimensional object design and fabrication, this paper explores the transformative potential at the intersection of biomaterials, biopolymers, and additive manufacturing. Drawing inspiration from the intricate designs found in the natural world, this study contributes to the evolving landscape of manufacturing and design paradigms. Biomimicry, rooted in emulating nature's sophisticated solutions, serves as the foundational framework for developing materials endowed with remarkable characteristics, including adaptability, responsiveness, and self-transformation. These advanced engineered biomimetic materials, featuring attributes such as shape memory and self-healing properties, undergo rigorous synthesis and characterization procedures, with the overarching goal of seamless integration into the field of additive manufacturing. The resulting synergy between advanced manufacturing techniques and nature-inspired materials promises to revolutionize the production of objects capable of dynamic responses to environmental stimuli. Extending beyond the confines of laboratory experimentation, these self-transforming objects hold significant potential across diverse industries, showcasing innovative applications with profound implications for object design and fabrication. Through the reduction of waste generation, minimization of energy consumption, and the reduction of environmental footprint, the integration of biomaterials, biopolymers, and additive manufacturing signifies a pivotal step towards fostering ecologically conscious design and manufacturing practices. Within this context, inanimate three-dimensional objects will possess the ability to transcend their static nature and emerge as dynamic entities capable of evolution, self-repair, and adaptive responses in harmony with their surroundings. The confluence of biomimicry and additive manufacturing techniques establishes a seminal precedent for a profound reconfiguration of contemporary approaches to design, manufacturing, and ecological stewardship, thereby decisively shaping a more resilient and innovative global milieu.

Bioinspired robot skin with mechanically gated electron channels for sliding tactile perception

Human-like tactile perception is critical for promoting robotic intelligence. However, reproducing tangential "sliding" perception of human skin is still struggling. Inspired by the lateral gating mechanosensing mechanism of mechanosensory cells, which perceives mechanical stimuli by lateral tension-induced opening-closing of ion channels, we report a robot skin (R-skin) with mechanically gated electron channels, achieving ultrasensitive and fast-response sliding tactile perception via pyramidal artificial fingerprint-triggered opening-closing of electron gates (E-gates, namely, customized V-shaped cracks within embedded mesh electron channels). By imitating cytomembrane to modulate membrane mechanics, local strain is enhanced at E-gates to effectively regulate electron pathways for high sensitivity while weakened at other positions to suppress random cracks for robust stability. The R-skin can directly recognize ultrafine surface microstructure (5 μm) at a response frequency (485 Hz) outshining humans and achieve human-like sliding perception functions, including dexterously distinguishing texture of complex-shaped objects and providing real-time feedback for grasping.

See Me, Feel Me, Touch Me, Heal Me: A Contextual Overview of Conductive Polymer Composites as Synthetic Human Skin

The fields of polymer science, conductive composites, materials engineering, robotics, and human perception intersect at the development and application of synthetic human skin. To be accepted by human users, artificial human skin must meet several requirement benchmarks. Synthetic human skin must look realistic, but not be eerie or creepy, upsetting those using or interacting with the material. Synthetic skin must feel like human skin, including mechanical response, thermal conductivity, and tactile properties. Realistic synthetic human skin must be electrically conductive, so that the user may experience accurate sensations of touch and feel. Finally, synthetic human skin should possess some degree of self-healing behavior. This review provides a brief description of advances in these disparate aspects of synthetic skin science, from the perspective of a practicing conductive polymer composite scientist and engineer.

Tactile Interaction Sensor with Millimeter Sensing Acuity

In this article we report on a 3 × 3 mm tactile interaction sensor that is able to simultaneously detect pressure level, pressure distribution, and shear force direction. The sensor consists of multiple mechanical switches under a conducting diaphragm. An external stimulus is measured by the deflection of the diaphragm and the arrangement of mechanical switches, resulting in low noise, high reliability, and high uniformity. Our sensor is able to detect tactile forces as small as ~50 mgf along with the direction of the shear force. It also distinguishes whether there is a normal pressure during slip motion. We also succeed in detecting the contact shape and the contact motion, demonstrating potential applications in robotics and remote input interfaces. Since our sensor has a simple structure and its function depends only on sensor dimensions, not on an active sensing material, in comparison with previous tactile sensors, our sensor shows high uniformity and reliability for an array-type integration.

Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition

As a surrogate for human tactile cognition, an artificial tactile perception and cognition system are proposed to produce smooth/soft and rough tactile sensations by its user's tactile feeling; and named this system as "tactile avatar". A piezoelectric tactile sensor is developed to record dynamically various physical information such as pressure, temperature, hardness, sliding velocity, and surface topography. For artificial tactile cognition, the tactile feeling of humans to various tactile materials ranging from smooth/soft to rough are assessed and found variation among participants. Because tactile responses vary among humans, a deep learning structure is designed to allow personalization through training based on individualized histograms of human tactile cognition and recording physical tactile information. The decision error in each avatar system is less than 2% when 42 materials are used to measure the tactile data with 100 trials for each material under 1.2N of contact force with 4cm s-1 of sliding velocity. As a tactile avatar, the machine categorizes newly experienced materials based on the tactile knowledge obtained from training data. The tactile sensation showed a high correlation with the specific user's tendency. This approach can be applied to electronic devices with tactile emotional exchange capabilities, as well as advanced digital experiences.

A Non-Array Type Cut to Shape Soft Slip Detection Sensor Applicable to Arbitrary Surface

The presence of a tactile sensor is essential to hold an object and manipulate it without damage. The tactile information helps determine whether an object is stably held. If a tactile sensor is installed at wherever the robot and the object touch, the robot could interact with more objects. In this paper, a skin type slip sensor that can be attached to the surface of a robot with various curvatures is presented. A simple mechanical sensor structure enables the cut and fit of the sensor according to the curvature. The sensor uses a non-array structure and can operate even if a part of the sensor is cut off. The slip was distinguished using a simple vibration signal received from the sensor. The signal is transformed into the time-frequency domain, and the slippage was determined using an artificial neural network. The accuracy of slip detection was compared using four artificial neural network models. In addition, the strengths and weaknesses of each neural network model were analyzed according to the data used for training. As a result, the developed sensor detected slip with an average of 95.73% accuracy at various curvatures and contact points.

Development of Fully Flexible Tactile Pressure Sensor with Bilayer Interlaced Bumps for Robotic Grasping Applications

Flexible tactile sensors have been utilized in intelligent robotics for human-machine interaction and healthcare monitoring. The relatively low flexibility, unbalanced sensitivity and sensing range of the tactile sensors are hindering the accurate tactile information perception during robotic hand grasping of different objects. This paper developed a fully flexible tactile pressure sensor, using the flexible graphene and silver composites as the sensing element and stretchable electrodes, respectively. As for the structural design of the tactile sensor, the proposed bilayer interlaced bumps can be used to convert external pressure into the stretching of graphene composites. The fabricated tactile sensor exhibits a high sensing performance, including relatively high sensitivity (up to 3.40% kPa-1), wide sensing range (200 kPa), good dynamic response, and considerable repeatability. Then, the tactile sensor has been integrated with the robotic hand finger, and the grasping results have indicated the capability of using the tactile sensor to detect the distributed pressure during grasping applications. The grasping motions, properties of the objects can be further analyzed through the acquired tactile information in time and spatial domains, demonstrating the potential applications of the tactile sensor in intelligent robotics and human-machine interfaces.