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Multifunctional Soft Robotic Finger Based on a Nanoscale Flexible Temperature–Pressure Tactile Sensor for Material Recognition
... However, these actuators are not adapted to soft grippers designed to pick and place objects in specific locations. Pneumatic grippers equipped with piezoresistive force sensors have also been proposed [12][13][14][15][16]. To be specific, 3D-printable conductive elastomer-based sensor was attached onto a pneumatic actuator for a grasping demonstration and showed its piezoresistive effect [12]. ...
... To elaborate the gripping movement of a soft robotic hand in combination with a temperature sensor, a force sensor was suggested with a silicone rubber, single-walled carbon nanotubes (SWCNTs), and silver threads [13]. A soft robotic finger was made with the encapsulation of a sponge-based pressure sensor and a nanowirebased temperature sensor [14]. A 3D-printed soft gripper was tested with a soft force sensor consisting of MWCNTs for the analysis of its gripping force [15]. ...
A pneumatic soft gripper, composed of multiple elastomeric materials, was designed and manufactured based on gripping simulations. The simulation results demonstrated that the different stiffnesses of the elastomeric materials can influence the internal air pressure required for the proper actuation of the gripper. Considering the substrate properties and the morphological changes of the soft gripper during gripping, a piezoresistive force sensor was developed using elastomers and conductive filaments with the aid of additive manufacturing techniques. We confirmed the reproducibility and stability of the proposed piezoresistive force sensor through evaluations under various fabrication conditions. Results from touch experiments and compressive force measurements indicated that the stiffness of the sensor substrate and the thickness of the conductive part of the sensor affected the sensitivity and reliability of the sensor with respect to different levels of applied forces. Incorporating a rigid panel between the soft gripper and the piezoresistive force sensor diminished the effect of the variable stiffness and curvature of the gripper on the measurement of electrical resistance generated by the piezoresistive force sensor. Our 3D-printed sensor combined with elastomeric materials showed the possibility of differentiating the simple actuation and the gripping demonstration of the soft gripper.
... • Temperature sensors: Temperature sensors are sensors that measure the temperature of a material or environment. They are commonly used in robotic fingers to monitor the temperature of the motors and other components of the finger [102]. • Pressure sensors: Pressure sensors measure the pressure of a fluid or gas. ...
... • Pressure sensors: Pressure sensors measure the pressure of a fluid or gas. They are commonly used in robotic fingers for sensing the fluid pressure used in hydraulic or pneumatic actuators [2], [102]. Table 7 shows some rigid sensors' applications, advantages, and limitations. ...
This review provides a comprehensive analysis of recent advancements in the development and applications of robotic fingers. The review focuses on four critical components: mechanism, actuation, sensor and control. A thorough literature search was conducted to identify and evaluate relevant studies, and the results were synthesized and analyzed to provide an overview of the field’s current state. The review highlights major contributions, trends, and gaps in the literature and critically evaluates the strengths and limitations of the reviewed studies. The discussion section explores the implications of the findings, including future directions that need to be addressed. The review concludes with a forward-looking outlook on the significance of the field and its potential impact on mechatronics. Overall, this review offers a unique and original contribution to the field by providing a comprehensive overview of the latest developments in robotic fingers.
... In recent years, to obtain tactile information accurately and efficiently, kinds of tactile sensors have been designed based on various working principles. The main types are: piezoresistive [2]- [5], capacitive [6]- [8], optical [9]- [11], magnetic [12]- [14], piezoelectric [15]- [17], barometric [18], [19], visual [20]- [30], etc. These sensors facilitate high-precision tactile perception in mimicing mechanoreceptors of human skins. ...
... This sensor was designed with a spatial resolution of 15 micrometers in spacing and 6 micrometers in height and achieved a 98.9% recognition accuracy rate for 20 types of commercial textiles under random sliding velocities. In [8], a tactile sensor with a sandwich-like structure was created by using PET film as the conductive layer and PEDOT/PSS conductive sponge as the dielectric layer. This sensor was embedded in the fingertips of a pneumatic soft finger, for the identification of more than ten different material surfaces. ...
Tactile sensing, which serves as a modality parallel to vision and auditory, provides rich contact information that is irreplaceable by other modalities. Although tactile sensing technology has made great progress over past decades, existing sensors still lag far behind human-skins in infinite-resolution sensing, large-area sensing, and thinness. Inspired by the bionic mechanism of human skins that embedding various receptors into soft tissues, here we design a low-cost and super-resolution tactile sensor by embedding flexible pressure sensors into a soft silicone layer. Different to the traditional functional imitating of human receptors (e.g., Pacinian corpuscle), our focus is on the selection of the soft silicone materials to better mimic the soft tissues of human skins. When an external force is applied on the soft silicone layer, the deformation of the soft silicone can excite the response of multiple pressure sensors, which mimic the Pacinian corpuscles in human skins. Based on experimental data and practical applicability, the optimal parameters for the soft silicone layer are determined to enable more responsed corpuscles for the same contact force. Then the position and magnitude of the normal force are estimated based on a reconstruction algorithm to achieve super-resolution and larger-area sensing. In addition, a human-computer interaction interface for signal collection and tactile real-time display is designed to vividly show the contact status. Experiments show that the tactile sensor can achieve normal force estimation with an average error of 0.61 N and millimeter-level super-resolution localization within a range of 22.8mm × 22.8mm. Moreover, our sensor is more compact (only 6mm in thickness) than visuo-tactile sensors (15mm), which are the current state-of-the-art.
... 8 In addition, background noise, occlusion, and other factors also affect the accuracy of visual object recognition. 9 On the other hand, touchbased recognition utilizes tactile sensors based on various sensing principles of vision, 10 piezoresistive, 1,11-23 piezoelectric, 24,25 capacitive, [26][27][28] triboelectric, 1,2,[16][17][18][29][30][31][32][33][34][35][36] magnetic, 37,38 and thermosensitive 4,19,39 to detect softness, texture, roughness, temperature, or thermal conductivity of objects. Using multimodal tactile information incorporated with machine learning algorithms, robots recognize objects in much greater detail. ...
... It is a great difficulty to build a generalized recognition model learned from the limited prior samples to accurately recognize new untrained (unseen) objects belonging to the same categories as the trained samples. Although some approaches [17][18][19]29,[33][34][35]40 report high accuracies in recognizing objects that have been trained, few studies obtain good recognition for new untrained (unseen) objects. The poor generalization of robotic tactile recognition greatly restricts its practical applications. ...
Since tactile sensing provides rich and delicate sensations, touch-based object recognition has attracted public attention and has been extensively developed for robots. However, robotic grasping recognition in real-life scenarios is highly challenging due to the complexity of real-life objects in shapes, sizes, and other details, as well as the uncertainty of real grabs in orientations and locations. Here, we propose a novel robotic tactile sensing method, utilizing the spatiotemporal sensing of multimodal tactile sensors acquired during hand grasping to simultaneously perceive multi-attributes of the grasped object, including thermal conductivity, thermal diffusivity, surface roughness, contact pressure, and temperature. Multimodal perception of thermal attributes (thermal conductivity, diffusivity, and temperature) and mechanical attributes (roughness and contact pressure) greatly enhance the robotic ability to recognize objects. To further overcome the complexity and uncertainty in real-life grasping recognition, inspired by human logical reasoning “from easy to hard” in solving puzzles, we propose a novel cascade classifier using multilayered long short-term memory neural networks to hierarchically identify objects according to their features. With the enhanced multimodal perception ability of tactile sensors and the novel cascade classifier, the robotic grasping recognition achieves a high recognition accuracy of 98.85% in discriminating diverse garbage objects, showing excellent generalizability. The proposed spatiotemporal tactile sensing with logical reasoning strategy overcomes the difficulty of robotic object recognition in complex real-life scenes and facilitates its practical applications in our daily lives.
... Li et al. [21] introduced a tactile sensor with a multi-layer structure; combined with machine learning algorithms, a robotic hand with ten sensors achieved a 94% recognition rate in waste sorting tasks. Yang et al. [22] proposed multi-layer tactile sensors integrated on a soft robotic hand, utilizing artificial neural networks to accurately identify 13 different materials under high contact pressures of 1.3-1.9 kPa. Lee et al. [23] developed an intelligent thermo-calorimeter (TCM) as a thermal sensing unit, successfully distinguishing various materials, especially metals, with high precision. ...
... where t represents time, k o and α o are the thermal conductivity and thermal diffusivity of the tested material, and f h denotes the theoretical heat transfer model. In this study, 67 different types of metals and non-metals were selected [22,31,32], with thermal conductivity ranging from 0.06 to 405.5 W·m −1 ·K −1 , covering the parameter range of common materials, as shown in Figure 5. To enhance the training efficiency of the BP neural network, feature selection and data preprocessing were conducted on the training dataset. ...
Thermal feedback plays an important role in tactile perception, greatly influencing fields such as autonomous robot systems and virtual reality. The further development of intelligent systems demands enhanced thermosensation, such as the measurement of thermal properties of objects to aid in more accurate system perception. However, this continues to present certain challenges in contact-based scenarios. For this reason, this study innovates by using the concept of semi-infinite equivalence to design a thermosensation system. A discrete transient heat transfer model was established. Subsequently, a data-driven method was introduced, integrating the developed model with a back propagation (BP) neural network containing dual hidden layers, to facilitate accurate calculation for contact materials. The network was trained using the thermophysical data of 67 types of materials generated by the heat transfer model. An experimental setup, employing flexible thin-film devices, was constructed to measure three solid materials under various heating conditions. Results indicated that measurement errors stayed within 10% for thermal conductivity and 20% for thermal diffusion. This approach not only enables quick, quantitative calculation and identification of contact materials but also simplifies the measurement process by eliminating the need for initial temperature adjustments, and minimizing errors due to model complexity.
... Furthermore, in [18], tactile and vision sensors were utilized in the learning process, with only the vision data used during the recognition phase to avoid sensor deterioration. Moreover, multimodal sensors, including pressure, vibration, temperature, etc., have also been developed [19]- [24] to improve the sensing performance. ...
... Therefore, high-accuracy recognition independent of the initial temperature is a challenging issue, and thermal-based recognition is sensitive to environmental changes and is mainly used as a subsidiary and complementary element of multimodal sensing. These studies [24], [40] tackled the issue; however, more investigation in terms of various initial temperatures in the training and test phases is needed to improve the thermalbased method. The authors believe that improvements in thermal sensing significantly advance multimodal sensing techniques. ...
Thermal properties are significant for recognizing an object’s material but cannot be determined via visual and stiffness (or tactile) –based recognition techniques. Most studies have used temperature as a complementary part of multimodal sensing; however, the thermal signal is an unexplored capability that can be beneficial for recognizing target objects. Since changes in thermal responses can result from both material properties and initial temperature, realizing robust and high-accuracy recognition in different environments is a challenging issue. To tackle the issue, this paper proposes a novel strategy for material identification that can actively measure heat flow by heating and cooling a robot gripper, enabling the extraction of the thermal properties of contact materials regardless of the object’s initial temperature variation (referred to as “active heat flow sensing”). We use a robotic task as an example of one possible application of the proposed strategy. For this, we developed a gripper pad embedded in a temperature control system and heat flow sensor to monitor the thermal exchange during contact with a target object. The paper conducted some experiments divided into two scenarios. The first experimental results show that active heat flow sensing is realized within 0.4 sec from first contact for 100 % classification of four heated materials. The second experimental results show that the three materials, whose thermal properties are largely different, can be classified within 0.7 sec from first contact using different initial temperatures of the training and test data. These results suggest robustness against environmental change, which has been difficult using conventional temperature-based methods.
... So, the control of soft robotic flexible bodies is achieved through structural computation, primarily relying on the material's inherent properties [24] and the matrix node that signifies its change. Soft robotic bodies face a significant challenge pertaining to the intricate modeling and design of dynamic control within a precise algorithm [25]. It is imperative to integrate sensors within the structure of soft robotic bodies in order to achieve precise sensing feedback, thereby facilitating the maintenance of critical control mechanisms [26]. ...
The importance of bio-robotics has been increasing day by day. Researchers are trying to mimic nature in a more creative way so that the system can easily adapt to the complex nature and its environment. Hence, bio-robotic grippers play a role in the physical connection between the environment and the bio-robotics system. While handling the physical world using a bio-robotic gripper, complexity occurs in the feedback system, where the sensor plays a vital role. Therefore, a human-centered gripper sensor can have a good impact on the bio-robotics field. But categorical classification and the selection process are not very systematic. This review paper follows the PRISMA methodology to summarize the previous works on bio-robotic gripper sensors and their selection process. This paper discusses challenges in soft robotic systems, the importance of sensing systems in facilitating critical control mechanisms, along with their selection considerations. Furthermore, a classification of soft actuation based on grippers has been introduced. Moreover, some unique characteristics of soft robotic sensors are explored, namely compliance, flexibility, multifunctionality, sensor nature, surface properties, and material requirements. In addition, a categorization of sensors for soft robotic grippers in terms of modalities has been established, ranging from the tactile and force sensor to the slippage sensor. Various tactile sensors, ranging from piezoelectric sensing to optical sensing, are explored as they are of the utmost importance in soft grippers to effectively address the increasing requirements for intelligence and automation. Finally, taking everything into consideration, a flow diagram has been suggested for selecting sensors specific to soft robotic applications.
... Nevertheless, piezoresistive pressure sensors are expensive, cannot be mass-produced, and often exhibit poor stability [17,18]. In addition, there has been a drive to further increase the sensitivity of flexible pressure sensors so that they can be incorporated into sensing devices for the detection of other external signals, such as temperature and humidity [19,20]. To improve the sensitivity, it is important to tune the microstructure of the dielectric layer, which increases the manufacturing complexity of the sensor. ...
The use of flexible pressure sensors has become increasingly widespread in a variety of applications, including wearable electronics and electronic skin. These sensors need to exhibit high sensitivity, wide detection limits, a fast response time, a linear response, and mechanical stability. In this study, we demonstrate a resistive pressure sensor based on randomly arranged micropyramid polydimethylsiloxane (PDMS) with a conductive poly(3,4-ethylenedioxythiophene): polystyrenesulfonate (PEDOT:PSS) thin film with a sensitivity of 391 kPa⁻¹, a response time of 52.91 ms, a recovery time of 4.38 ms, and a limit of detection (LOD) of 0.35 kPa. Electrodes are then connected to a pair of the proposed resistive pressure sensors that face each other to fabricate a pressure sensing device. We examine various characteristics of the fabricated device, including the changes observed when applying loads ranging from 0 to 2.58 kPa. The proposed sensor exhibits high sensitivity and a rapid response time.
... Traditional robots have heavily relied on visual perception, while seldom considering the tactile senses that are necessary for interaction in complex and dynamic environments [7][8][9][10] . Leveraging principles such as piezoelectric [11][12][13][14] , piezoresistive [15][16][17][18][19] , triboelectric 3,20-22 , capacitive 5,[23][24][25] , and thermosensitive [26][27][28] , tactile sensors fuse various tactile attributes such as pressure, temperature, texture, and material properties, providing robots with rich senses and enabling them to interact with the environment more dexterously. In manufacturing, robots equipped with tactile sensors would execute fine assembly tasks with higher precision and adaptability 29 . ...
As robots are increasingly participating in our daily lives, the quests to mimic human abilities have driven the advancements of robotic multimodal senses. However, current perceptual technologies still unsatisfied robotic needs for home tasks/environments, particularly facing great challenges in multisensory integration and fusion, rapid response capability, and highly sensitive perception. Here, we report a flexible tactile sensor utilizing thin-film thermistors to implement multimodal perceptions of pressure, temperature, matter thermal property, texture, and slippage. Notably, the tactile sensor is endowed with an ultrasensitive (0.05 mm/s) and ultrafast (4 ms) slip sensing that is indispensable for dexterous and reliable grasping control to avoid crushing fragile objects or dropping slippery objects. We further propose and develop a robotic tactile-visual fusion architecture that seamlessly encompasses multimodal sensations from the bottom level to robotic decision-making at the top level. A series of intelligent grasping strategies with rapid slip feedback control and a tactile-visual fusion recognition strategy ensure dexterous robotic grasping and accurate recognition of daily objects, handling various challenging tasks, for instance grabbing a paper cup containing liquid. Furthermore, we showcase a robotic desktop-cleaning task, the robot autonomously accomplishes multi-item sorting and cleaning desktop, demonstrating its promising potential for smart housekeeping.
... 1,2 Pressure sensors have become the most widely used sensors for many new flexible applications, such as medical machines, 3,4 electronic skin, 5,6 and soft robotics. 7 Flexible capacitive pressure sensors have attracted more and more attention due to their low power consumption. 8 Innovating sensitive mechanisms and developing new sensitive materials contribute a lot to the continued development of flexible capacitive sensors. ...
In this paper, an intelligent insole that contains five wide-range flexible capacitive pressure sensors is developed. The output signal of these five sensors is collected and processed by a portable microprocessor system, which is then transmitted to a cloud platform via a Wi-Fi module. The ensuing data visualization is constructed with a WeChat mini-program. The wide-range flexibility is achieved by employing composition materials with a high pressure-sensitive effect. A novel approach is proposed to fabricate flexible pressure-sensitive dielectrics, thereby significantly enhancing the sensitivity and detection range of pressure sensors. The fabrication process involves utilizing polydimethylsiloxane (PDMS) as a flexible substrate, incorporating nano-iron powder and polyvinylidene fluoride as sensitizing materials, and applying an external magnetic field to control the distribution of iron nanoparticles during the curing process of PDMS. Furthermore, a motion detection system tailored for these flexible sensors is developed. By integrating sensor networks with Internet of things technology, the application potential of wide-range flexible pressure sensors in kinematics and medical rehabilitation fields can be effectively realized.
In recent years, as wearable electronics continue to advance toward flexible, lightweight, and versatile designs, flexible pressure sensors with wide response ranges and high sensitivity have shown tremendous research value and application potential. In this study, we fabricated TPU-based flexible pressure sensors with a multistage gradient porous structure using layer-by-layer freezing and solvent templating techniques. Due to the layered differences in Young’s modulus from varying porosities, these sensors exhibit high pressure sensitivity (S, SMAX = 34.08 MPa⁻¹) and can accurately distinguish stresses across a wide range (0–1.2 MPa). Additionally, they demonstrate rapid response and recovery times (140 ms), durability over 3000 compression cycles, and the ability to detect both subtle movements (facial expressions and swallowing) and larger actions (joint bends, walking, and running). Furthermore, we developed a smart glove using these gradient-structured pressure sensors combined with a K-nearest neighbor (KNN) algorithm, enabling accurate identification of various fruit types. Notably, the TPU sensors also exhibit excellent thermal insulation and Joule heating properties, making them effective for human thermal management even in extreme temperatures.
Flexible pressure sensors with high sensitivity and a wide detection range must be developed for practical applications. In this study, a dual‐active‐layer flexible piezoresistive sensor was developed. A reduced graphene oxide film with wrinkled microstructures was prepared by a simple and low‐cost substrate pre‐stretching method and used as the first active layer. A thermoplastic polyurethane electrospun fiber membrane was modified by fast polydopamine coating and ultrasonication with multi‐walled carbon nanotubes and used as the second active layer. Owing to the continuously changing conductive pathways created by the wrinkled microstructures and fiber network under pressure deformation, the sensor achieved a detection range of 0–100 kPa, with sensitivities of 8.5, 1.35, and 0.39 kPa⁻¹ in the ranges of 0–1, 1–20, and 20–100 kPa, respectively. Additionally, the sensor exhibited a low detection limit (2 Pa), response and recovery times of 105 and 85 ms, respectively, and reliable service performance over 10,000 loading/unloading cycles. The sensor enabled real‐time monitoring of finger and wrist bending, beaker‐holding, and fingertip‐sliding on a touch screen, demonstrating its feasible applications in wearable electronics and human–machine interface devices.
The presence of electromagnetic interference (EMI) leads to distortion of current and voltage waveforms, which reduces the accuracy and stability of sensor devices. The emergence of flexible electronic devices has broken the limits of physical space, as they can be bent and twisted at will. However, this characteristic exacerbates unwanted coupling of their internal sensing elements, which can interfere with each other. At present, the solution to EMI is based on electromagnetic shielding (EMS), but this method alone cannot solve internal EMI of flexible sensor devices. In this study, the gallium-based liquid metal (LM) circuits are printed on the Ecoflex@Fe film to realize a stretchable film with both EMS and wave-absorbing functions, which is expected to simultaneously address the effects of internal and external EMI. The results show that the shielding efficiency of the electromagnetic wave shielding and absorbing (EWSA) film is as high as 54.5 dB on one side, while the reflection loss on the other side is as low as −43.5 dB. In addition, the LM-based EWSA film maintains positive wave-absorbing and EMS properties during stretching in different directions and it can also effectively avoid EMI after 1000 times of stretching. Overall, the LM-based EWSA film, which enables broadband EMS and wave-absorption, provides a solution for the development of next-generation flexible electronic skin that eliminates both internal and external EMI.
The sensing principles, performance, and applications of the iontronic sensor in posture assessment in this work.
Tactile sensing, which serves as a modality parallel to vision and auditory, provides rich contact information that is irreplaceable by other modalities. Although tactile sensing technology has made great progress over past decades, existing sensors still lag far behind human skin in infinite-resolution sensing, large-area sensing, and thinness. Inspired by the bionic mechanism of human skin that has various receptors embedded into soft tissues, here we design a low-cost and super-resolution tactile sensor by embedding flexible pressure sensors into a soft silicone layer. Different to the traditional functional imitation of human receptors (e.g., Pacinian corpuscle), our focus is on the selection of the soft silicone materials to better mimic the soft tissues of human skin. When an external force is applied on the soft silicone layer, the deformation of the soft silicone can excite the response of multiple pressure sensors, which mimic the Pacinian corpuscles in human skin. Based on experimental data and practical applicability, the optimal parameters for the soft silicone layer are determined to enable more responsed Bionic human receptors for the same contact force. Then the position and magnitude of the normal force are estimated based on a reconstruction algorithm to achieve super-resolution and larger-area sensing. In addition, a human-computer interaction interface for signal collection and tactile real-time display is designed to vividly show the contact status. Experiments show that the tactile sensor can achieve normal force estimation with an average error of 0.61 N and millimeter-level super-resolution localization within a range of
mm. Moreover, our sensor is more compact (only 6 mm in thickness) than visuo-tactile sensors (15 mm), which are the current state-of-the-art.
Over the past decades, tactile sensing technology has made significant advances in the fields of health monitoring and robotics. Compared to conventional sensors, self‐powered tactile sensors do not require an external power source to drive, which makes the entire system more flexible and lightweight. Therefore, they are excellent candidates for mimicking the tactile perception functions for wearable health monitoring and ideal electronic skin (e‐skin) for intelligent robots. Herein, the working principles, materials, and device fabrication strategies of various self‐powered tactile sensing platforms are introduced first. Then their applications in health monitoring and robotics are presented. Finally, the future prospects of self‐powered tactile sensing systems are discussed.
Flexible pressure sensors have a wide range of applications including human body monitoring and robotic control. Recent work has focused on developing pressure sensors that excel at measuring pressure in the ultrasensitive range, often with parallel plate piezocapacitive sensors and a dielectric that relies on microstructures. However, these approaches have a few drawbacks including a limited range and high complexity leading to expensive and time-consuming manufacturing. To mitigate these problems, we demonstrate the fabrication of a low-cost, flexible, interdigitated electrode (IDE) pressure sensor with an overlaid layered elastomer composed of polydimethylsiloxane (PDMS) and Barium Titanate (BaTiO3). The elastomers are manipulated by modifying the mixing ratio, curing temperature, incorporation of BaTiO3, and compressed at two strain rates. Characterization of these elastomers and IDE geometry allows for insights into the behavior and tunability of the layered macrostructure and electrode design. As a result, the leading IDE geometry can be tuned to work in a lower range with a sensitivity of 77.8% per decade between 0 and 10 kPa and 4.5% per decade between 10 and 100 kPa or in a larger range with a sensitivity of 12.9% per decade between 0 and 100 kPa and 3.4% per decade between 100 and 500kPa.
Flexible dual‐mode sensors play a pivotal role in information exchange between humans and the environment. However, achieving dual‐mode sensing encompassing both flexibility and stretchability, while accurately quantifying stimulus signals such as temperature, remains a significant challenge. This paper presents a novel flexible dual‐mode strain/temperature sensor (DMSTS) that utilizes graphite powder (GR)/polyaniline (PANI)/silicone rubber composites, inspired by the bionic microstructure of a centipede's foot. The DMSTS exhibits an exceptional strain detection range (≈177%), and a low limit of detection (0.5% strain). Regarding temperature sensing, the DMSTS demonstrates a positive temperature coefficient effect within the range of 25–90 °C, with an ultrahigh sensitivity of 10.3 within the 75–90 °C range. Leveraging the photothermal characteristics of GR and PANI, the DMSTS holds significant promise for applications in human motion detection, infrared imaging, and photothermal effects. When integrated into an intelligent sensing system, it enables dynamic noncontact temperature measurement, human micro‐expression detection, and motion joint monitoring. Additionally, by incorporating a flexible thermochromic film with color‐changing ink, the DMSTS transforms temperature detection into a visually intuitive operation. With its versatile dual‐mode sensing capabilities, the DMSTS exhibits substantial potential in the fields of wearable electronics and healthcare.
Rapid deployment of automation in today's world has opened up exciting possibilities in the realm of design and fabrication of soft robotic grippers endowed with sensing capabilities. Herein, a novel design and rapid fabrication by 3D printing of a mechano‐optic force sensor with a large dynamic range, sensitivity, and linear response, enabled by metamaterials‐based structures, is presented. A simple approach for programming the metamaterial's behavior based on mathematical modeling of the sensor under dynamic loading is proposed. Machine learning models are utilized to predict the complete force–deformation profile, encompassing the linear range, the onset of nonlinear behavior, and the slope of profiles in both bending and compression‐dominated regions. The design supports seamless integration of the sensor into soft grippers, enabling 3D printing of the soft gripper with an embedded sensor in a single step, thus overcoming the tedious and complex and multiple fabrication steps commonly applied in conventional processes. The sensor boasts a fine resolution of 0.015 N, a measurement range up to 16 N, linearity (adj. R²–0.991), and delivers consistent performance beyond 100 000 cycles. The sensitivity and range of the embedded mechano‐optic force sensor can be easily programmed by both the metamaterial structure and the material's properties.
The development of functional textiles combining conventional apparel with advanced technologies for personal health management (PHM) has garnered widespread attention. However, the current PHM textiles often achieve multifunctionality by stacking functional modules, leading to poor durability and scalability. Herein, a scalable and robust PHM textile is designed by integrating electrical, radiative, and solar heating, electromagnetic interference (EMI) shielding, and piezoresistive sensing performance onto cotton fabric. This is achieved through an uncomplicated screen‐printing process using silver paste. The conductivity of the PHM textile is ≈1.6 × 10⁴ S m⁻¹, ensuring an electric heating temperature of ≈134 °C with a low voltage of 1.7 V, as well as an EMI shielding effectiveness of ≈56 dB, and human motion monitoring performance. Surprisingly, the radiative/solar heating capability of the PHM textile surpasses that of traditional warm leather. Even after undergoing rigorous physical and chemical treatments, the PHM textile maintains terrific durability. Additionally, the PHM textile possesses maneuverable scalability and comfortable wearability. This innovative work opens up new avenues for the strategic design of PHM textiles and provides an advantageous guarantee of mass production.
As a kind of flexible electronic device, flexible pressure sensor has attracted wide attention in medical monitoring and human‐machine interaction. With the continuous deepening of research, high‐sensitivity sensor is developing from single function to multi‐function. However, Current multifunctional sensors lack the ability to integrate joule heating, detect sliding friction, and self‐healing. Herein, a MXene/polyurethane (PU) flexible pressure sensor with a self‐healing property for joule heating and friction sliding is fabricated. The MXene/PU sensitive layer with special spinosum structure is prepared by a simple spraying method. After face‐to‐face assembly of the sensitive layers, the MXene/PU flexible pressure sensor is obtained and showed excellent sensitivity (150.65 kPa⁻¹), fast response/recovery speed (75.5/63.9 ms), and good stability (10 000 cycles). Based on the self‐healing property of PU, the sensor also has the ability to heal after mechanical damage. In addition, the sensor realizes the joule heating function under low voltage, and has the real‐time monitoring ability of sliding objects. Combined with low cost and simple manufacturing method, the multi‐functional MXene/PU flexible sensor shows a wide range of application potential in human activity monitoring, thermal management, and slip recognition.
The soft hand allows for flexible and safe object grasping by utilizing tactile sensitivity to gather information about the object, thereby minimizing potential damage to its surface. However, the integration design of the drive and sensor faces significant challenges due to variations in driving mode and substrate material properties. This research presents a soft hand design based on liquid crystal elastomer (LCE) integrated with a capacitive pressure sensor in the finger. The finger-bending part of the soft hand is composed of a liquid crystal elastomer driven by a low-pressure (6V) electric heating film, and the finger sensor component consists of a flexible capacitive pressure sensor with a grid-like structure of electrodes and a PU sponge medium. Among them, the electric heating film is prepared from polyimide (PI) with imprinted gate electrodes, and the flexible capacitive sensor is prepared from an electrode composed of liquid crystal elastomers with an imprinted grid structure and filled with multi-walled carbon nanotubes, with a porous PU sponge as the medium. The flexible capacitive pressure sensor has a sensitivity of up to 0.06875 kPa
−1
in the low-pressure range. This method of integrating the sensor on a liquid-crystal elastomer film achieves pressure sensing and demonstrates the potential of liquid-crystal elastomer films for gripping objects and sensing recognition applications.
Sensing pressure and temperature are two important functions of human skin that integrate different types of tactile receptors. In this paper, a deformable artificial flexible multi‐stimulus‐responsive sensor is demonstrated that can distinguish mechanical pressure from temperature by measuring the impedance and the electrical phase at the same frequency without signal interference. The electrical phase, which is used for measuring the temperature, is totally independent of the pressure by controlling the surface micro‐shapes and the ion content of the ionic film. By doping the counter‐ion exchange reagent into the ionic liquid before pouring, the upper temperature measuring limit increases from 35 to 50 °C, which is higher than the human body temperature and the ambient temperature on Earth. The sensor shows high sensitivity to pressure (up to 0.495 kPa⁻¹) and a wide temperature sensing range (−10 to 50 °C). A multimodal ion‐electronic skin (IEM‐skin) with an 8 × 8 multi‐stimulus‐responsive sensor array is fabricated and can successfully sense the distribution of temperature and pressure at the same time. Finally, the sensors are used for monitoring the touching motions of a robot‐arm finger controlled by a remote interactive glove and successfully detect the touching states and the temperature changes of different objects.
Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.
Inspired by the function of human skin, a flexible tactile sensor was assembled based on the novel IL/SWCNT/PEDOT:PSS nanocomposite, which possesses the multisensory ability to independently identify pressure and temperature with no cross-coupling.
Flexible tactile sensors with multifunctional sensing functions have attracted much attention due to their wide applications in artificial limbs, intelligent robots, human‐machine interfaces, and health monitoring devices. Here, a multifunctional flexible tactile sensor based on resistive effect for simultaneous sensing of pressure and temperature is reported. The sensor features a simple design with patterned metal film on a soft substrate with cavities and protrusions. The decoupling of pressure and temperature sensing is achieved by the reasonable arrangement of metal layers in the patterned metal film. Systematically experimental and numerical studies are carried out to reveal the multifunctional sensing mechanism and show that the proposed sensor exhibits good linearity, fast response, high stability, good mechanical flexibility, and good microfabrication compatibility. Demonstrations of the multifunctional flexible tactile sensor to monitor touch, breathing, pulse and objects grabbing/releasing in various application scenarios involving coupled temperature/pressure stimuli illustrate its excellent capability of measuring pressure and temperature simultaneously. These results offer an effective tool for multifunctional sensing of pressure and temperature and create engineering opportunities for applications of wearable health monitoring and human‐machine interfaces.
Underwater perception of a broad range of force holds great importance in aquatic explorative activities, while flexible tactile sensors face technical challenges to realize. This paper presents a novel flexible aquatic tactile sensor based on waterproof graphene (GR)/carbon nanotube (CNT)/Polydimethylsiloxane (PDMS) composites. The prepared GR/CNT/PDMS composites possess excellent hydrophobic and electromechanical properties with a water contact angle over 134° and an ultrahigh gauge factor of 2296, making them an ideal piezoresistive sensing material for underwater broad‐range force sensing. The proposed tactile sensor has 3 × 3 sensing units and uses dual interlocked water‐ripple structures to improve its sensitivity and force detection range. The fabricated tactile sensor is characterized by two distinct sensitivities: a high sensitivity of 0.0338 kPa⁻¹ at 0.062–150 kPa and a low sensitivity of 0.00357 kPa⁻¹ at 150–450 kPa. Further, the sensor exhibited excellent resistance response, fast dynamic recovery, and both mechanical and electrical stability in aquatic environments. Then, the aquatic tactile sensor is worn on the palm of the human hand to detect the distribution and variation of contact forces when grasping objects with different shapes and hardness, demonstrating the potential underwater applications of the developed aquatic tactile sensor for broad‐range force sensing.
Advances in material sciences, control algorithms, and manufacturing techniques have facilitated rapid progress in soft grippers, propelling their adoption in various fields. In this review article, a comprehensive overview of the design and control aspects of intelligent soft robotic grippers tailored specifically for agricultural product handling is provided. Soft grippers have emerged as a promising solution for handling delicate and fragile objects. In this article, the recent progress in various gripper design, including fluidic and mechanical grippers, is elucidated and the role of advanced control approaches in enabling intelligent functions, such as object classification and grasping condition evaluation, is explored. Moreover, the challenges and opportunities pertaining to implementation of soft grippers in the agricultural industry are thoroughly discussed. While most demonstrations of soft grippers and their control strategies remain at the experimental stage, in this article, it is aimed to provide insights into the potential applications of soft grippers in agricultural product handling, thereby inspiring future research in this field.
Wearable devices developed with flexible electronics have great potential applications for human health monitoring and motion sensing. Although material softness and structural flexibility provide a deformable human-machine interface to adapt to joint bending or tissue stretching/compression, flexible sensors are inconvenient in practical uses as they usually require calibration every time they are installed. This article presents an approach to design and fabricate a flexible curvature sensor to measure human articular movements for amphibious applications. This flexible sensor employs the capacitive sensing principle, where the dielectric layer and electrodes are made from the polyurethane resin and eutectic gallium-indium (EGaIn) liquid metal; and the fabrication process is implemented with shape deposition molding for batch production. The sensing method for articular rotation angles employs the Euler beam model to make the sensor reusable after one-time calibration by compensating for the unpredicted manual installation error. The illustrative application to ankle sensing in amphibious gaits shows that the root-mean-square error is within 5° for different walking speeds (0.7-1.1 m/s) in treadmill tests and the maximum error is within 3° for underwater sensing with quasi-static measurements. It is expected that the proposed waterproof flexible sensor can push the boundaries of wearable robotics, human locomotion, as well as their related applications.
Achieving highly accurate responses to external stimuli during human motion is a considerable challenge for wearable devices. The present study leverages the intrinsically high surface‐to‐volume ratio as well as the mechanical robustness of nanostructures for obtaining highly‐sensitive detection of motion. To do so, highly‐aligned nanowires covering a large area were prepared by capillarity‐based mechanism. The nanowires exhibit a strain sensor with excellent gauge factor (≈35.8), capable of high responses to various subtle external stimuli (≤200 µm deformation). The wearable strain sensor exhibits also a rapid response rate (≈230 ms), mechanical stability (1000 cycles) and reproducibility, low hysteresis (<8.1%), and low power consumption (<35 µW). Moreover, it achieves a gauge factor almost five times that of microwire‐based sensors. The nanowire‐based strain sensor can be used to monitor and discriminate subtle movements of fingers, wrist, and throat swallowing accurately, enabling such movements to be integrated further into a miniaturized analyzer to create a wearable motion monitoring system for mobile healthcare.
Low dimension poly(3,4-ethylenedioxythiophene) poly (styrenesulfonate) (PEDOT: PSS) has been applied as resistor-type devices for temperature sensing applications. However, their response speed and thermal sensitivity is still not good enough for practical application. In this work, we proposed a new strategy to improve the thermal sensing performance of PEDOT: PSS by combined micro/nano confinement and materials doping. The dimension effect is carefully studied by fabricating different sized micro/nanowires through a low-cost printing approach. It was found that response speed can be regulated by adjusting the surface/volume (S/V) ratio of PEDOT: PSS. The fastest response (<3.5 s) was achieved by using nanowires with a maximum S/V ratio. Besides, by doping PEDOT: PSS nanowires with Graphene oxide (GO), its thermo-sensitivity can be maximized at specific doping ratio. The optimized nanowires-based temperature sensor was further integrated as a flexible epidermal electronic system (FEES) by connecting with wireless communication components. Benefited by its flexibility, fast and sensitive response, the FEES was demonstrated as a facile tool for different mobile healthcare applications.
Facile fabrication and high ambient stability are strongly desired for the practical application of temperautre sensor in real-time wearable healthcare. Herein, a fully printed flexible temperature sensor based on cross-linked poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) was developed. By introducing the crosslinker of (3-glycidyloxypropyl)trimethoxysilane (GOPS) and the fluorinated polymer passivation (CYTOP), significant enhancements in humidity stability and temperature sensitivity of PEDOT:PSS based film were achieved. The prepared sensor exhibited excellent stability in environmental humidity ranged from 30% RH to 80% RH, and high sensitivity of −0.77% °C−1 for temperature sensing between 25 °C and 50 °C. Moreover, a wireless temperature sensing platform was obtained by integrating the printed sensor to a printed flexible hybrid circuit, which performed a stable real-time healthcare monitoring.
Development of wearable devices for continuous respiration monitoring is of great importance for evaluating human health. Here, we propose a new strategy to achieve rapid respiration response by confining conductive polymers into 1D nanowires which facilitates the water molecules absorption/desorption and maximizes the sensor response to moisture. The nanowires arrays were fabricated through a low-cost nanoscale printing approach on flexible substrate. The nanoscale humidity sensor shows a high sensitivity (5.46%) and ultrafast response (0.63 s) when changing humidity between 0 and 13% and can tolerate 1000 repetitions of bending to a curvature radius of 10 mm without influencing its performance. Benefited by its fast response and low power assumption, the humidity sensor was demonstrated to monitor human respiration in real time. Different respiration patterns including normal, fast and deep respiration can be distinguished accurately.
Multisensory tactile systems play an important role in enhancing robot intelligence. A competent robotic tactile system needs to be simple in structure and easily operated, especially with multiple sensations, and have good coordinate ability like human skin. A novel multisensory tactile system for humanoid robotic hands is proposed, allowing the hand to identify objects by grasping and manipulating them. Robotic multifunction sensors based on skin‐inspired thermosensation and structured with micro platinum ribbons partially covered with piezo‐thermic silver‐nanoparticle‐doped porous polydimethylsiloxane membrane simultaneously and independently detect contact pressure, local ambient temperature, and thermal conductivity and temperature of an object. Multiple tactile information which is obtained by the robotic sensors is fused comprehensively based on neural network classification to identify diverse objects in uncertain and dynamic gripping with an object recognition accuracy of 95%. This multisensory system enables robotic hand to better interact with its environment, enhances robotic intelligence, and makes various complex tasks feasible for robots, such as sorting material or rescuing from fire or other disasters.
The highly toxic hydrogen sulphide (H 2 S) present in air can cause negative effects on human health. Thus, monitoring of this gas is vital in gas leak alarms and security. Efforts have been devoted to the fabrication and enhancement of the H 2 S-sensing performance of gas sensors. Herein, we used electron beam evaporation to decorate nickel oxide (NiO) nanoparticles on the surface of tin oxide (SnO 2 ) nanowires to enhance their H 2 S gas-sensing performance. The synthesised NiO-SnO 2 materials were characterised by field-emission scanning electron microscopy, transmission electron microscopy and energy dispersive spectroscopy analysis. H 2 S gas-sensing characteristics were measured at various concentrations (1-10 ppm) at 200-350 °C. The results show that with effective decoration of NiO nanoparticles, the H 2 S gas-sensing characteristics of SnO 2 nanowires are significantly enhanced by one or two orders compared with those of the bare material. The sensors showed an effective response to low-level concentrations of H 2 S in the range of 1-10 ppm, suitable for application in monitoring of H 2 S in biogas and in industrial controls. We also clarified the sensing mechanism of the sensor based on band structure and sulphurisation process.
Recent work has begun to explore the design of biologically inspired soft robots composed of soft, stretchable materials for applications including the handling of delicate materials and safe interaction with humans. However, the solid-state sensors traditionally used in robotics are unable to capture the high-dimensional deformations of soft systems. Embedded soft resistive sensors have the potential to address this challenge. However, both the soft sensors—and the encasing dynamical system—often exhibit nonlinear time-variant behavior, which makes them difficult to model. In addition, the problems of sensor design, placement, and fabrication require a great deal of human input and previous knowledge. Drawing inspiration from the human perceptive system, we created a synthetic analog. Our synthetic system builds models using a redundant and unstructured sensor topology embedded in a soft actuator, a vision-based motion capture system for ground truth, and a general machine learning approach. This allows us to model an unknown soft actuated system. We demonstrate that the proposed approach is able to model the kinematics of a soft continuum actuator in real time while being robust to sensor nonlinearities and drift. In addition, we show how the same system can estimate the applied forces while interacting with external objects. The role of action in perception is also presented. This approach enables the development of force and deformation models for soft robotic systems, which can be useful for a variety of applications, including human-robot interaction, soft orthotics, and wearable robotics.
The fabrication of nanowire (NW)‐based flexible electronics including wearable energy storage devices, flexible displays, electrical sensors, and health monitors has received great attention both in fundamental research and market requirements in our daily lives. Other than a disordered state after synthesis, NWs with designed and hierarchical structures would not only optimize the intrinsic performance, but also create new physical and chemical properties, and integration of individual NWs into well‐defined structures over large areas is one of the most promising strategies to optimize the performance of NW‐based flexible electronics. Here, the recent developments and achievements made in the field of flexible electronics composed of integrated NW structures are presented. The different assembly strategies for the construction of 1D, 2D, and 3D NW assemblies, especially the NW coassembly process for 2D NW assemblies, are comprehensively discussed. The improvements of different NW assemblies on flexible electronics structure and performance are described in detail to elucidate the advantages of well‐defined NW assemblies. Finally, a short summary and outlook for future challenges and perspectives in this field are presented. Directional assembly of nanowires into 1D, 2D, and 3D assemblies toward flexible electronic devices benefits many potential applications. 1D assemblies with fiber structures can be used as flexible electronics for textiles, 2D assemblies can be used as transparent electrodes or units for logic circuits, and 3D assemblies can be used in the fabrication of pressure sensors or high‐performance energy storage devices.
Gas nanosensors, comprised of arrays of nanoelectrodes with finger-widths of ~100 nm developed by electron beam lithography and aerosol assisted chemical vapor deposited non-functionalized and Pt-functionalized tungsten oxide nanowires (<100 nm) subsequently integrated across the pairs of electrodes via dielectrophoresis method, are developed in this work. The functionality of these devices is validated towards various concentrations of NO2 and C2H5OH. Results demonstrate reproducible and consistent responses with better sensitivity and partial selectivity for the non-functionalized systems to NO2, as opposed to the Pt-functionalized systems, which display better sensing properties towards C2H5OH with a loss of response to NO2, that, in turn, increases the cross-sensitivity between these gases. These results are explained on the basis of the additional chemical and electronic interactions at the Pt/tungsten oxide interface, which increase the pre-adsorption of oxygen species and make the functionalized surface rather more sensitive to C2H5OH than to NO2, in contrast to the non-functionalized surface.
Resistive devices composed of one dimensional nanostructures are promising candidate for next generation gas sensors. However, the large-scale fabrication of nanowires is still a challenge, restricting the commercialization of such type of devices. Here, we reported a highly efficient and facile approach to fabricate poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) nanowire chemiresistive type of gas sensor by nanoscale soft lithography. Well-defined sub-100 nm nanowires are fabricated on silicon substrate which facilitates the device integration. The nanowire chemiresistive gas sensor is demonstrated for NH3 and NO2 detection at room-temperature and shows a limit of detection at ppb level which is compatible with nanoscale PEDOT:PSS gas sensors fabricated with conventional lithography technique. In comparison with PEDOT:PSS thin film gas sensor, the nanowire gas sensor exhibits a higher sensitivity and much faster response to gas molecules.
Some materials feel colder to the touch than others, and we can use this difference in perceived coldness for material recognition. This review focuses on the mechanisms underlying material recognition based on thermal cues. It provides an overview of the physical, perceptual, and cognitive processes involved in material recognition. It also describes engineering domains in which material recognition based on thermal cues have been applied. This includes haptic interfaces that seek to reproduce the sensations associated with contact in virtual environments and tactile sensors the aim for automatic material recognition. The review concludes by considering the contributions of this line of research in both science and engineering.
Epidermal electronic systems (EESs) are skin-like electronic systems, which can be used to measure several physiological parameters from the skin. This paper presents materials and a simple, straightforward fabrication process for skin-conformable inkjet-printed temperature sensors. Epidermal temperature sensors are already presented in some studies, but they are mainly fabricated using traditional photolithography processes. These traditional fabrication routes have several processing steps and they create a substantial amount of material waste. Hence utilizing printing processes, the EES may become attractive for disposable systems by decreasing the manufacturing costs and reducing the wasted materials. In this study, the sensors are fabricated with inkjet-printed graphene/PEDOT:PSS ink and the printing is done on top of a skin-conformable polyurethane plaster (adhesive bandage). Sensor characterization was conducted both in inert and ambient atmosphere and the graphene/PEDOT:PSS temperature sensors (thermistors) were able reach higher than 0.06% per degree Celsius sensitivity in an optimal environment exhibiting negative temperature dependence.
Despite the emergence of flexible and stretchable actuators, few possess sensing capabilities. Here, we present a facile method of integrating a flexible pneumatic actuator with stretchable strain sensor to form a soft sensorized actuator. The elastomeric actuator comprises a microchannel connected to a controlled air source to achieve bending. The strain sensor comprises a thin layer of screen-printed silver nanoparticles on an elastomeric substrate to achieve its stretchability and flexibility while maintaining excellent conductivity at ≈8 Ω sq–1. By printing a mesh network of conductive structures, our strain sensor is able to detect deformations beyond 20% with a high gauge factor beyond 50 000. The integration of a pneumatic soft actuator with our sensing element enables the measurement of the extent of actuator bending. To demonstrate its potential as a rehabilitation sensing actuator, we fit the sensorized actuator in a glove to further analyze finger kinematics. With this, we are able to detect irregular movement patterns in real time and assess finger stiffness or dexterity.
The excellent compliance and large range of motion of soft actuators controlled by fluid pressure has lead to strong interest in applying devices of this type for biomimetic and human-robot interaction applications. However, in contrast to soft actuators fabricated from stretchable silicone materials, conventional technologies for position sensing are typically rigid or bulky and are not ideal for integration into soft robotic devices. Therefore, in order to facilitate the use of soft pneumatic actuators in applications where position sensing or closed loop control is required, a soft pneumatic bending actuator with an integrated carbon nanotube position sensor has been developed. The integrated carbon nanotube position sensor presented in this work is flexible and well suited to measuring the large displacements frequently encountered in soft robotics. The sensor is produced by a simple soft lithography process during the fabrication of the soft pneumatic actuator, with a greater than 30% resistance change between the relaxed state and the maximum displacement position. It is anticipated that integrated resistive position sensors using a similar design will be useful in a wide range of soft robotic systems.
The detection of biological and chemical species is central to many areas of healthcare and the life sciences, ranging from uncovering and diagnosing disease to the discovery and screening of new drug molecules. Hence, the development of new devices that enable direct, sensitive, and rapid analysis of these species could impact humankind in significant ways. Devices based on nanowires are emerging as a powerful and general class of ultrasensitive, electrical sensors for the direct detection of biological and chemical species.
This paper presents a feasibility study of a central pattern generator-based analog controller for an autonomous robot. The operation of a neuronal circuit formed of electronic neurons based on Hindmarsh–Rose neuron dynamics and first order chemical synapses is modeled. The controller is based on a standard CMOS process with 2 V supply voltage. In order to achieve low power consumption, CMOS subthreshold circuit techniques are used. The controller generates an excellent replica of the walking motor program and allows switching between walking in different directions in response to different command inputs.The simulated power consumption is 4.8 mW and die size including I/O pads is 2.2 mm by 2.2 mm. Simulation results demonstrate that the proposed design can generate adaptive walking motor programs to control the legs of autonomous robots.
The objective of these two experiments was to determine the role of thermal cues in material discrimination and localization, using materials that spanned a range of thermal properties. In the first experiment, the subjects were required to select the cooler of two materials presented to the index fingers. In the second, the finger that was in contact with a material that was different from that presented to the other two fingers on the same hand had to be identified. The results indicated that the subjects were able to discriminate between materials, using thermal cues, when the differences in their thermal properties were large. The changes in skin temperature when the fingers were touching the materials were, however, smaller than those predicted by the theoretical model. The ability to localize the thermal changes when three fingers on the same hand were stimulated was poor and depended on both the thermal properties of the target and the distractor materials.
The ability to produce distributed sensors by tailoring materials readily available on the market is becoming an emerging strategy for Internet of Things applications. Embedding sensors into functional substrates allows one to reduce costs and improve integration and gives unique functionalities inaccessible to silicon or other conventional materials used in microelectronics. In this paper, we demonstrate the functionalization of a commercial polyurethane (PU) foam with the conductive polymer PEDOT:PSS: the resulting material is a modified all-polymeric foam where the internal network of pores is uniformly coated with a continuous layer of PEDOT:PSS acting as a mechanical transducer. When an external force causes a modification of the foam microstructure, the conductivity of the device varies accordingly, enabling the conversion of a mechanical pressure into an electric signal. The sensor provides a nearly linear response when stimulated by an external pressure in the range between 0.1 and 20 kPa. Frequency-dependent measurements show a useful frequency range up to 20 Hz. A simple micromechanical model has been proposed to predict the device performance based on the characteristics of the system, including geometrical constrains, the microstructure of the polymeric foam, and its elastic modulus. By taking advantage of the simulation output, a flexible shoe in sole prototype has been developed by embedding eight pressure sensors into a commercial PU foam. The proposed device may provide critical information to medical teams, such as the real-time bodyweight distribution and a detailed representation of the walking dynamic.
Robot hands with tactile perception can improve the safety of object manipulation and also improve the accuracy of object identification. Here, we report the integration of quadruple tactile sensors onto a robot hand to enable precise object recognition through grasping. Our quadruple tactile sensor consists of a skin-inspired multilayer microstructure. It works as thermoreceptor with the ability to perceive thermal conductivity of a material, measure contact pressure, as well as sense object temperature and environment temperature simultaneously and independently. By combining tactile sensing information and machine learning, our smart hand has the capability to precisely recognize different shapes, sizes, and materials in a diverse set of objects. We further apply our smart hand to the task of garbage sorting and demonstrate a classification accuracy of 94% in recognizing seven types of garbage.
Discrimination of surface textures and their surface roughness using tactile sensors have attracted increasing attention. Highly sensitive tactile sensors with the ability to recognize and discriminate the surface textures and roughness of grasped objects are crucial for intelligent robotics. This paper presents a methodology by using the developed WMB model (W-M function and Beam-Bundle Theory) and an algorithm based on artificial neural network to study the performance of a flexible tactile sensor for surface texture classification. For the WMB model, the quasi-3D surfaces of specific objects are reconstructed based on W-M function and basic statistical theory. A simplified Beam-Bundle Model is utilized to represent the cover layer of the sensor and simulates the normal force fluctuations during sliding movements. According to the simulation results, surface textures can be classified by the characteristic frequency cluster (CFC) existing in the fluctuation of curve’s spectrum. As an experiment, an artificial neural network is established to classify surface textures based on voltage signals from the tactile sensor. An MAF array represents the CFC information and improves the classification accuracy from 78 % to 82 %. The results demonstrate the effectiveness of the proposed WMB model and that it provides a new method of analysis involving robotic tactile interactions.
There has been a great deal of interest in designing soft robots that can mimic a human system with haptic and proprioceptive functions. There is now a strong demand for soft robots that can sense their surroundings and functions in harsh environments. This is because the wireless sensing and actuating capabilities of these soft robots are very important for monitoring explosive gases in disaster areas and for moving through contaminated environments. To develop these wireless systems, complex electronic circuits must be integrated with various sensors and actuators. However, the conventional electronic circuits based on silicon are rigid and fragile, which can limit their reliable integration with soft robots for achieving continuous locomotion. In our study, we developed an untethered, soft robotic hand that mimics human fingers. The soft robotic fingers are composed of a thermally responsive elastomer composite that includes capsules of ethanol and liquid metals for its shape deformation through an electrothermal phase transition. And these soft actuators are integrated fully with flexible forms of heaters, with pressure, temperature, and hydrogen gas sensors, and wireless electronic circuits. Entire functions of this soft hand, including the gripping motion of soft robotic fingers and the real-time detections of tactile pressures, temperatures, and hydrogen gas concentrations, are monitored or controlled wirelessly using a smartphone. This wireless sensing and actuating system for somatosensory and respiratory functions of a soft robot provides a promising strategy for next-generation robotics.
Flexible and wearable pressure sensors are of paramount importance for development of personalized medicine and electronic skin. However, the preparation of easily disposed pressure sensors is still facing with pressing challenges. Herein, we have developed an all paper-based piezoresistive (APBP) pressure sensor through a facile, cost-effective and environment-friendly method. This pressure sensor was based on tissue paper coated with silver nanowires (AgNWs) as sensing material, nanocellulose paper (NCP) as bottom substrate for printing electrodes, and NCP as top encapsulating layer. The APBP pressure sensor showed high sensitivity of 1.5 kPa-1 in the range of 0.3-30.2 kPa and retained excellent performance in bending state. Furthermore, the APBP sensor has been mounted on the human skin to monitor human physiological signals (such as arterial heart pulse and pronunciation from throat) and successfully applied as soft electronic skin to response to external pressure. Due to the use of common tissue paper, NCP, AgNWs and conductive nanosilver ink only, the pressure sensor has low-cost, facile-craft and fast-preparation advantages and can be disposed easily by incineration. We believe that the developed sensor will propel the advance of easily disposed pressure sensor and green paper-based flexible electronic devices.
We develop a flexible and multifunctional resistive sensor integrating uniform conductive coating layers with interlaced nanofibrous structure through a large-scale and cost-efficient strategy. Elastomer nanofiber framework not only endows superior flexibility for the multi-mode sensor, but also provides abundant contact sites and contact area which can significantly enhance the sensitivity and operating range of obtained sensor. More impressively, the multilevel sensing paths comprised of both interlaminar and intrastratal signal transmissions fulfill the simultaneous and precise detection of pressure-temperature stimuli without interference to each other. The achieved sensor ultimately shows an ultrahigh pressure sensitivity of 1185.8 kPa-1 and superior reliability, enabling the rapid detection of subtle stimulus as low as 2.4 Pa and superior response behavior under 5000 cyclic loading tests. Besides, high linearity and stability are achieved for temperature sensing characteristic even under various pressure loadings. These outstanding performances are further evaluated by preparing 4×5 bimodal sensor array to synchronously monitor multiple signals, consequently demonstrating precise sensing capability with negligible interference and providing effective approach for developing multiparametric sensing platforms and wearable devices.
Flexible and wearable pressure sensors have attracted tremendous attention due to their wider applications such as human-interfacing and healthcare monitoring. However, it is a great challenge to achieve accurate pressure detection and stability against external stimuli (in particular, bending deformation) over a wide range of pressure from tactile to body weight levels. Here, we introduce an ultrawide-range, bending-insensitive, and flexible pressure sensor based on a carbon nanotube (CNT) network-coated thin porous elastomer sponge for use in human interface devices. The integration of the CNT networks into three dimensional (3D) microporous elastomers provides high deformability and a large change of contact between the conductive CNT networks due to the presence of micropores, thereby improving the sensitivity compared with that obtained using CNTs-embedded solid elastomers. As electrical pathways are continuously generated up to high compressive strain (~80%), the pressure sensor shows an ultrawide pressure-sensing range (10 Pa-1.2 MPa) while maintaining favorable sensitivity (0.01-0.02 kPa-1) and linearity (R2 ~0.98). Also, the pressure sensor exhibits excellent electromechanical stability and insensitivity to bending-induced deformations. Finally, we demonstrate that the pressure sensor can be applied in a flexible piano pad as an entertainment human interface device and a flexible foot insole as a wearable healthcare and gait monitoring device, respectively.
Glucose metabolism plays an important role in cell energy supply, and quantitative detection of intracellular glucose level is particularly important for understanding many physiological processes. Glucose electrochemical sensors are widely used for blood and extracellular glucose detection. However, intracellular glucose detection cannot be achieved by these sensors owing to their large size and consequent low spatial resolution. Herein, we developed a single nanowire glucose sensor for electrochemical detection of intracellular glucose by depositing Pt nanoparticles (Pt NPs) on a SiC@C nanowire and further immobilizing glucose oxidase (GOD) there on. Glucose was converted by GOD to an electroactive product H2O2 which was further electro-catalyzed by Pt NPs. The glucose nanowire sensor is endowed with high sensitivity, high spatial-temporal resolution and enzyme specificity due to its nanoscale size and enzymatic reaction. This allows the real-time monitoring of the intracellular glucose level, and the increasement of intracellular glucose level induced by a novel potential hypoglycemic agent, reinforcing its potential application in lowering the blood glucose level. This work provides a versatile method for the construction of enzyme-modified nanosensors to electrochemically detect intracellular non-electroactive molecules, which is of great benefit to the physiological and pathological studies.
Recently, cellulose paper based materials are emerging for applications in wearable “green” electronics due to their earth-abundance, low cost, light weight, flexibility, and sustainability. Herein, for the first time, we develop an almost all cellulose paper based pressure sensor through a facile, cost-effective, scalable, and environment-friendly approach. The screen-printed interdigital electrodes on the flat printing paper and the carbonized crepe paper (CCP) with a good conductivity are integrated into a flexible pressure sensor as substrates and active materials, respectively. The porous and corrugated structure of the CCP endows the pressure sensor with high sensitivity (2.56-5.67 KPa⁻¹ in the range of 0-2.53 KPa), wide workable pressure range (0-20 KPa), fast response time (<30 ms), low detection limit (~0.9 Pa), and good durability (>3000 cycles). Additionally, we demonstrate the practical applications of the CCP pressure sensor in detection of finger touching, wrist pulse, respiration, phonation, and acoustic vibration, etc., and real-time monitoring of spatial pressure distribution. The proposed CCP pressure sensor has great potentials in various applications as wearable electronics. Moreover, the subtle fabrication of desired materials based on commercially available products provides new insights into the development of green electronics.
Flexible and wearable pressure sensor may offer convenient, timely, and portable solutions to human motion detection, yet it is a challenge to develop cost-effective materials for pressure sensor with high compressibility and sensitivity. Herein, a cost-efficient and scalable approach is reported to prepare highly flexible and compressible conductive sponge for piezoresistive pressure sensor. The conductive sponge, PEDOT:PSS@MS, is prepared by one-step dip coating the commercial melamine sponge (MS) in an aqueous dispersion of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). Due to the interconnected porous structure of MS, the conductive PEDOT:PSS@MS has high compressibility and stable piezoresistive response at the compressive strain up to 80%, as well as good reproducibility over 1000 cycles. Thereafter, versatile pressure sensors fabricated using the conductive PEDOT:PSS@MS sponges are attached to the different parts of human body; the capabilities of these devices to detect a variety of human motions including speaking, finger bending, elbow bending, and walking are evaluated. Furthermore, prototype tactile sensory array based on these pressure sensors is demonstrated.
Humans possess manual dexterity, motor skills, and other physical abilities that rely on feedback provided by the somatosensory system. Herein, a method is reported for creating soft somatosensitive actuators (SSAs) via embedded 3D printing, which are innervated with multiple conductive features that simultaneously enable haptic, proprioceptive, and thermoceptive sensing. This novel manufacturing approach enables the seamless integration of multiple ionically conductive and fluidic features within elastomeric matrices to produce SSAs with the desired bioinspired sensing and actuation capabilities. Each printed sensor is composed of an ionically conductive gel that exhibits both long-term stability and hysteresis-free performance. As an exemplar, multiple SSAs are combined into a soft robotic gripper that provides proprioceptive and haptic feedback via embedded curvature, inflation, and contact sensors, including deep and fine touch contact sensors. The multimaterial manufacturing platform enables complex sensing motifs to be easily integrated into soft actuating systems, which is a necessary step toward closed-loop feedback control of soft robots, machines, and haptic devices.
In this study, we demonstrate a fabrication of highly sensitive flexible temperature sensor with a bioinspired octopus-mimicking adhesive. A resistor-type temperature sensor consisting of a composite of poly(N isopropylacrylamide) (pNIPAM)-temperature sensitive hydrogel, poly(3,4 ethylenedioxythiophene) polystyrene sulfonate, and carbon nanotubes, exhibits a very high thermal sensitivity of 2.6%•ºC⁻¹ between 25 and 40 °C so that the change in skin temperature of 0.5 °C can be accurately detected. At the same time, the polydimethylsiloxane adhesive layer of octopus-mimicking rim structure coated with pNIPAM, is fabricated through the formation of a single mold by utilizing undercut phenomenon in photolithography. The fabricated sensor shows stable and reproducible detection of skin-temperature under repeated attachment/detachment cycles onto skin without any skin irritation for a long time. This work suggests a high potential application of our skin-attachable temperature sensor to wearable devices for medical and healthcare monitoring.
Identification of the material from which an object is made is of significant value for effective robotic grasping and manipulation. Characteristics of the material can be retrieved using different sensory modalities: vision based, tactile based or sound based. Compressibility, surface texture and thermal properties can each be retrieved from physical contact with an object using tactile sensors. This paper presents a method for collecting data using a biomimetic fingertip in contact with various materials and then using these data to classify the materials both individually and into groups of their type. Following acquisition of data, principal component analysis (PCA) is used to extract features. These features are used to train seven different classifiers and hybrid structures of these classifiers for comparison. For all materials, the artificial systems were evaluated against each other, compared with human performance and were all found to outperform human participants’ average performance. These results highlighted the sensitive nature of the BioTAC sensors and pave the way for research that requires a sensitive and accurate approach such as vital signs monitoring using robotic systems.
Working together, heated and unheated temperature sensors can recognize contact with different materials and contact with the human body. As such, distributing these sensors across a robot's body could be beneficial for operation in human environments. We present a stretchable fabric-based skin with force and thermal sensors that is suitable for covering areas of a robot's body, including curved surfaces. It also adds a layer of compliance that conforms to manipulated objects, improving thermal sensing. Our open hardware design addresses thermal sensing challenges, such as the time to heat the sensors, the efficiency of sensing, and the distribution of sensors across the skin. It incorporates small self-heated temperature sensors on the surface of the skin that directly make contact with objects, improving the sensors’ response times. Our approach seeks to fully cover the robot's body with large force sensors, but treats temperature sensors as small, point-like sensors sparsely distributed across the skin. We present a mathematical model to help predict how many of these point-like temperature sensors should be used in order to increase the likelihood of them making contact with an object. To evaluate our design, we conducted tests in which a robot arm used a cylindrical end effector covered with skin to slide objects and press on objects made from four different materials. After assessing the safety of our design, we also had the robot make contact with the forearms and clothed shoulders of 10 human participants. With 2.0 s of contact, the actively-heated temperature sensors enabled binary classification accuracy over 90% for the majority of material pairs. The system could more rapidly distinguish between materials with large differences in their thermal effusivities (e.g., 90% accuracy for pine wood vs. aluminum with 0.5 s of contact). For discrimination between humans vs. the four materials, the skin's force and thermal sensing modalities achieved 93% classification accuracy with 0.5 s of contact. Overall, our results suggest that our skin design could enable robots to recognize contact with distinct task-relevant materials and humans while performing manipulation tasks in human environments.
Approaching to the super-sensitivity, we herein develop a pressure sensor based on fully bubbled ultralight graphene block through a simple sparkling strategy. The obtained sparking graphene block (SGB) exhibits excellent elasticity even at 95% compressive strain and rebounds a steel ball with an ultra-fast recovery speed (~1085 mm s−1). Particularly, the SGB based sensor reveals a record pressure sensitivity of 229.8 kPa−1, much higher than other graphene materials due to the highly cavity-branched internal structure. Impressively, the pressure sensor can detect the extremely gentle pressures even beyond the real human skin, promising for ultrasensitive sensing applications.
In this review, PEDOT-PSS is mainly a commercially available PEDOT-PSS, which is a water-dispersible form of the intrinsically conducting PEDOT doped with the water-soluble PSS, including its derivatives, copolymers, analogs (PEDOT:PSSs), even their composites via the chemical or physical modification toward the structure of PEDOT and/or PSS. First, we will focus on discussing the scientific importance of PEDOT-PSS in conjunction with its extraordinary properties and broad multidisciplinary applications in organic/polymeric electronics and optoelectronics from the viewpoint of the historical development and the promising application of representative ECPs. Subsequently, versatile film-forming techniques for the preparation of PEDOT-PSS film electrode were described in details, including common coating approaches and printing techniques, and many emerging preparative methods were mentioned. Then challenges (e.g., conductivity, stability in Water, adhesion to substrate electrode) of PEDOT-PSS film electrode for devices under the high humidity/watery circumstances, especially electrochemical devices are discussed. Fourth, we take PEDOT-PSS film electrode for a relatively new application in sensors as an example, mainly summarized advances in the development of various sensors based on PEDOT-PSSs and their composites in combination with its preparative methods and extraordinary properties. Finally, we give the outlook of PEDOT-PSS for possible applications with the emphasis on PEDOT-PSS film electrode for electrochemical devices, including sensors. (c) 2016 Wiley Periodicals, Inc.
Bending and pressure sensors are very essential for evaluating external stimuli in human motions; however, most of them are separate devices. Here, two orthogonal carbon nanotube–polyurethane sponge strips (CPSSs) are used, each of which has different resistances when bent or pressed, to fabricate a multi-functional stretchable sensor capable of detecting omnidirectional bending and pressure independently. Due to the shape of the strip, the resistance of CPSS changes differently when bent along different directions. Based on this feature, two perpendicular CPSSs can reflect information of both bending distance and bending direction. After basic measurement data are obtained, a function set can be formulated to calculate bending distance and bending direction simultaneously. The errors of bending distance and bending angle can be controlled to less than 4%. With the help of the triboelectric effect, which only happens when the device is pressed, the sensor can differentiate bending and pressure effectively, ensuring the device works in complex situations.
An ultra-stretchable and force-sensitive hydrogel with surface self-wrinkling microstructure is demonstrated by in situ synthesizing polyacrylamide (PAAm) and polyaniline (PANI) in closely packed swollen chitosan microspheres, exhibiting ultra-stretchability (>600%), high sensitivity (0.35 kPa(-1) ) for subtle pressures (<1 kPa), and can detect force in a broad range (10(2) Pa-10(1) MPa) with excellent electrical stability and rapid response speed, potentially finding applications for E-skin.
Stretchable and multifunctional sensors can be applied in multifunctional sensing devices, safety forewarning equipment, and multiparametric sensing platforms. However, a stretchable and multifunctional sensor was hard to fabricate until now. Herein, a scalable and efficient fabrication strategy is adopted to yield a sensor consisting of ZnO nanowires and polyurethane fibers. The device integrates high stretchability (tolerable strain up to 150%) with three different sensing capabilities, i.e., strain, temperature, and UV. Typically achieved specifications for strain detection are a fast response time of 38 ms, a gauge factor of 15.2, and a high stability of >10 000 cyclic loading tests. Temperature is detected with a high temperature sensitivity of 39.3% °C−1, while UV monitoring features a large ON/OFF ratio of 158.2. With its fiber geometry, mechanical flexibility, and high stretchability, the sensor holds tremendous prospect for multiparametric sensing platforms, including wearable devices.
Wearable human-interactive devices are advanced technologies that will improve the comfort, convenience, and security of humans, and have a wide range of applications from robotics to clinical health monitoring. In this study, a fully printed wearable human-interactive device called a “smart bandage” is proposed as the first proof of concept. The device incorporates touch and temperature sensors to monitor health, a drug-delivery system to improve health, and a wireless coil to detect touch. The sensors, microelectromechanical systems (MEMS) structure, and wireless coil are monolithically integrated onto flexible substrates. A smart bandage is demonstrated on a human arm. These types of wearable human-interactive devices represent a promising platform not only for interactive devices, but also for flexible MEMS technology.
Soft robots actuated by inflation of a pneumatic network (a “pneu-net”) of small channels in elastomeric materials are appealing for producing sophisticated motions with simple controls. Although current designs of pneu-nets achieve motion with large amplitudes, they do so relatively slowly (over seconds). This paper describes a new design for pneu-nets that reduces the amount of gas needed for inflation of the pneu-net, and thus increases its speed of actuation. A simple actuator can bend from a linear to a quasi-circular shape in 50 ms when pressurized at ΔP = 345 kPa. At high rates of pressurization, the path along which the actuator bends depends on this rate. When inflated fully, the chambers of this new design experience only one-tenth the change in volume of that required for the previous design. This small change in volume requires comparably low levels of strain in the material at maximum amplitudes of actuation, and commensurately low rates of fatigue and failure. This actuator can operate over a million cycles without significant degradation of performance. This design for soft robotic actuators combines high rates of actuation with high reliability of the actuator, and opens new areas of application for them.
This paper reports on the preliminary experimental results of using polydimethylsiloxane (PDMS) to manufacture a visual pulsating heat pipe with length, width and internal diameter of 56mm, 50mm and 2mm, respectively, including the manufacturing process, the vacuuming management for filling and packaging. The experiment used methanol and ethanol as working fluids. A fix filled ratio (about 60%) and different heating power values (3–8W) were used to test the thermal performance. A high-speed video camera was used to record the working situation of the working fluid inside the channel. The results are discussed and analyzed.The experiment shows that methanol, in a vertical orientation, shows the most efficient results. When the heating power is 3W, the thermal resistance is more than 4.5°C/W below the value for ethanol as the working fluid. For a heating power of 4W, the average temperature decreases to 15°C in the evaporator. Also, gravity will have an impact on the PHP performance: the vertical orientation is better as compared to the horizontal orientation.
silicon nanowires (SiNWs) with well orientation and crystallization are synthesized by the vapor-liquid-solid (VLS) process, and doped as n-type by an ex situ process using spin on dopant (SOD) technique. The ex situ doping process using SOD was based on solid-state diffusion, which comprised two stages: pre-coating and drive in. The phosphorous concentration in SiNWs was controlled by appropriate selections of the drive in temperature and the time period, which are 950 o C and 5-60 min in the present studies. The doped nanowire can be readily made into a temperature sensor with much better resolution and response. Calibration of the SiNW temperature sensor at different doping level has been performed. With a concentration of 4 x 10 15 atoms/cm 3 the SiNW sensor has the best temperature resolution (6186 :� / o C) and sensitivity in this study. Keywords-SiNWs; VLS synthesis; Ex situ doping; SOD;
We demonstrated the first application of a pyroelectric nanogenerator as a self-powered sensor (or active sensor) for detecting a change in temperature. The device consists of a single lead zirconate titanate (PZT) micro/nanowire that is placed on a thin glass substrate and bonded at its two ends, and it is packaged by polydimethylsiloxane (PDMS). By using the device to touch a heat source, the output voltage linearly increases with an increasing rate of change in temperature. The response time and reset time of the fabricated sensor are about 0.9 and 3 s, respectively. The minimum detecting limit of the change in temperature is about 0.4 K at room temperature. The sensor can be used to detect the temperature of a finger tip. The electricity generated under a large change in temperature can light up a liquid crystal display (LCD).
Electron microscopy studies are used to explore the morphology of thin poly(3,4-ethylenedioxythiophene) and polystyrene sulfonate acid (PEDOT:PSS) films. The figures show that the films are composed of grains with diameters in the range of about 50 nm. Energy dispersive X-ray spectroscopy analysis reveals that individual grains have a PEDOT-rich core and a PSS-rich shell with a thickness of about 5–10 nm. Atomic force microscopy (AFM) is then used to analyze the topography of fracture surfaces of ruptured PEDOT:PSS tensile specimens. These AFM scans also show that the films are composed of grains dispersed in a matrix. The investigations presented herein yield a picture of PEDOT:PSS morphology with unprecedented clarity.
