Structure-Foldable and Performance-Tailorable PI Paper-Based Triboelectric Nanogenerators Processed and Controlled by Laser-Induced Graphene.

Laser-induced graphene (LIG) technology has provided a new manufacturing strategy for the rapid and scalable assembling of triboelectric nanogenerators (TENG). However, current LIG-based TENG commonly rely on polymer films, e.g., polyimide (PI) as both friction material and carbon precursor of electrodes, which limit the structural diversity and performance escalation due to its incapability of folding and creasing. Using specialized PI paper composed of randomly distributed PI fibers to substantially enhance its foldability, this work creates a new type of TENG, which are structurally foldable and stackable, and performance tailorable. First, by systematically investigating the laser power-regulated performance of single-unit TENG, the open-circuit voltage can be effectively improved. By further exploiting the folding process, multiple TENG units can be assembled together to form multi-layered structures to continuously expand the open-circuit voltage from 5.3 to 34.4 V cm-2, as the increase of friction units from 1 to 16. Last, by fully utilizing the unique structure and performance, representative energy-harvesting and smart-sensing applications are demonstrated, including a smart shoe to recognize running motions and power LEDs, a smart leaf to power a thermometer by wind, a matrix sensor to recognize writing trajectories, as well as a smart glove to recognize different objects.

Clap-and-Fling Mechanism of Climbing-Flight Coccinella Septempunctata.

Previous studies on the clap-fling mechanism have predominantly focused on the initial downward and forward phases of flight in miniature insects, either during hovering or forward flight. However, this study presents the first comprehensive kinematic data of Coccinella septempunctata during climbing flight. It reveals, for the first time, that a clap-and-fling mechanism occurs during the initial upward and backward phase of the hind wings' motion. This discovery addresses the previously limited understanding of the clap-and-fling mechanism by demonstrating that, during the clap motion, the leading edges of beetle's wings come into proximity to form a figure-eight shape before rotating around their trailing edge to open into a "V" shape. By employing numerical solutions to solve Navier-Stokes (N-S) equations, we simulated both single hind wings' and double hind wings' aerodynamic conditions. Our findings demonstrate that this fling mechanism not only significantly enhances the lift coefficient by approximately 9.65% but also reduces the drag coefficient by about 1.7%, indicating an extension of the applicability range of this clap-and-fling mechanism beyond minute insect flight. Consequently, these insights into insect flight mechanics deepen our understanding of their biological characteristics and inspire advancements in robotics and biomimetics.

Flexible calorimetric flow sensor with unprecedented sensitivity and directional resolution for multiple flight parameter detection.

The accurate perception of multiple flight parameters, such as the angle of attack, angle of sideslip, and airflow velocity, is essential for the flight control of micro air vehicles, which conventionally rely on arrays of pressure or airflow velocity sensors. Here, we present the estimation of multiple flight parameters using a single flexible calorimetric flow sensor featuring a sophisticated structural design with a suspended array of highly sensitive vanadium oxide thermistors. The proposed sensor achieves an unprecedented velocity resolution of 0.11 mm·s-1 and angular resolution of 0.1°. By attaching the sensor to a wing model, the angles of attack and slip were estimated simultaneously. The triaxial flight velocities and wing vibrations can also be estimated by sensing the relative airflow velocity due to its high sensitivity and fast response. Overall, the proposed sensor has many promising applications in weak airflow sensing and flight control of micro air vehicles.

Teleoperation of an Anthropomorphic Robot Hand with a Metamorphic Palm and Tunable-Stiffness Soft Fingers.

Teleoperation in soft robotics can endow soft robots with the ability to perform complex tasks through human-robot interaction. In this study, we propose a teleoperated anthropomorphic soft robot hand with variable degrees of freedom (DOFs) and a metamorphic palm. The soft robot hand consists of four pneumatic-actuated fingers, which can be heated to tune stiffness. A metamorphic mechanism was actuated to morph the hand palm by servo motors. The human fingers' DOF, gesture, and muscle stiffness were collected and mapped to the soft robotic hand through the sensory feedback from surface electromyography devices on the jib. The results show that the proposed soft robot hand can generate a variety of anthropomorphic configurations and can be remotely controlled to perform complex tasks such as primitively operating the cell phone and placing the building blocks. We also show that the soft hand can grasp a target through the slit by varying the DOFs and stiffness in a trail.

Octopus-inspired sensorized soft arm for environmental interaction.

Octopuses can whip their soft arms with a characteristic "bend propagation" motion to capture prey with sensitive suckers. This relatively simple strategy provides models for robotic grasping, controllable with a small number of inputs, and a highly deformable arm with sensing capabilities. Here, we implemented an electronics-integrated soft octopus arm (E-SOAM) capable of reaching, sensing, grasping, and interacting in a large domain. On the basis of the biological bend propagation of octopuses, E-SOAM uses a bending-elongation propagation model to move, reach, and grasp in a simple but efficient way. E-SOAM's distal part plays the role of a gripper and can process bending, suction, and temperature sensory information under highly deformed working states by integrating a stretchable, liquid-metal-based electronic circuit that can withstand uniaxial stretching of 710% and biaxial stretching of 270% to autonomously perform tasks in a confined environment. By combining this sensorized distal part with a soft arm, the E-SOAM can perform a reaching-grasping-withdrawing motion across a range up to 1.5 times its original arm length, similar to the biological counterpart. Through a wearable finger glove that produces suction sensations, a human can use just one finger to remotely and interactively control the robot's in-plane and out-of-plane reaching and grasping both in air and underwater. E-SOAM's results not only contribute to our understanding of the function of the motion of an octopus arm but also provide design insights into creating stretchable electronics-integrated bioinspired autonomous systems that can interact with humans and their environments.

Atomistic Modeling of the Effect of Temperature on Interfacial Properties of 3D-Printed Continuous Carbon Fiber-Reinforced Polyamide 6 Composite: From Processing to Loading.

The combination of continuous fiber-reinforced thermoplastic composites (CFRTPCs) and the continuous fiber 3D printing (CF3DP) technique enables the rapid production of complex structural composites. In these 3D-printed composites, stress transfer primarily relies on the fiber-resin interface, making it a critical performance factor. The interfacial properties are significantly influenced by the temperatures applied during the loading and forming processes. While the effect of the loading temperature has been extensively researched, that of the forming temperature remains largely unexplored, especially from an atomistic perspective. Our research aims to employ molecular dynamics simulations to elucidate the effect of temperature on the interfacial properties of continuous carbon fiber-reinforced polyamide 6 (C/PA6) composites fabricated using the CF3DP technique, considering both loading and forming aspects. Through molecular dynamics simulations, we uncovered a positive correlation between the interfacial strength and forming temperature. Moreover, an increased forming temperature induced a notable shift in the failure mode of C/PA6 under uniaxial tensile loading. Furthermore, it was observed that increasing loading temperatures led to the deterioration of the mechanical properties of PA6, resulting in a gradual transition of the primary failure mode from adhesive failure to cohesive failure. This shift in the failure mode is closely associated with the glass transition of PA6.

Design and Finite Element Analysis of Artificial Braided Meniscus Model.

Currently, artificial meniscus prostheses are mostly homogenous, low strength, and difficult to mimic the distribution of internal fibers in the native meniscus. To promote the overall mechanical performance of meniscus prostheses, this paper designed a new artificial braided meniscus model and conducted finite element analysis. Firstly, we designed the spatial fiber interweaving structure of meniscus model to mimic the internal fiber distribution of the native meniscus. Secondly, we provided the detailed braiding steps and forming process principles based on the weaving structure. Thirdly, we adopted the models of the fiber-embedded matrix and multi-scale methods separately for finite element analysis to achieve the reliable elastic properties. Meanwhile, we compared the results for two models, which are basically consistent, and verified the accuracy of analysis. Finally, we conducted the comparative simulation analysis of the meniscus model and the pure matrix meniscus model based on the solved elastic constants through Abaqus, which indicated a 60% increase in strength.

Bending-Sensitive Optical Waveguide Sensor With Carbon-Fiber Layer for Monitoring Grip Strength.

With the gradual popularity of wearable devices, the demand for high-performance flexible wearable sensors is also increasing. Flexible sensors based on the optical principle have advantages e.g. anti-electromagnetic interference, antiperspirant, inherent electrical safety, and the potential for biocompatibility. In this study, an optical waveguide sensor integrating a carbon fiber layer, fully constraining stretching deformation, partly constraining pressing deformation, and allowing bending deformation, was proposed. The sensitivity of the proposed sensor is three times higher than that of the sensor without a carbon fiber layer, and good repeatability is maintained. We also attached the proposed sensor to the upper limb to monitor grip force, and the sensor signal showed a good correlation with grip force (the R-squared of the quadratic polynomial fitting was 0.9827) and showed a linear relationship when the grip force was greater than 10N (the R-squared of the linear fitting was 0.9523). The proposed sensor has the potential for applications in recognizing the intention of human movement to help the amputees control the prostheses.

Ultrasensitive Humidity Sensors with Synergy between Superhydrophilic Porous Carbon Electrodes and Phosphorus-Doped Dielectric Electrolyte.

Capacitive humidity sensors have been used for human health monitoring, but their performance may be poor in terms of sensitivity and response time, because of limitations in sensing materials and insufficient knowledge about sensing mechanisms. Herein, a new combination of humidity sensing materials to assemble thin-film based capacitive-type sensors is proposed by using PA-doped polybenzimidazole (PA-PBI) as an electrolyte and laser-carbonized PA-PBI as a carbon electrode (PA-PBI-C). Based on PA involved laser scribing, the flexible sensor can reach excellent humidity-sensing performances with an ultrahigh sensitivity (1.16 × 106 pF RH%-1, where RH represents the relative humidity), a superior linearity (R2 = 0.9982), a fast response time (0.72 s), and a low hysteresis in a wide RH range from 1% to 95%. By further studying P-O decorated porous carbon electrode with superhydrophilicity and the solid-state dielectric electrolyte featured by a high dielectric constant, a synergistic sensing mechanism consisting of a "Water reservoir" and a "Bridge" is established to support advanced health-monitoring applications such as the respiration patterns and skin condition where both sensitivity and response time are critical.

Laser-Induced Graphene Enabled Additive Manufacturing of Multifunctional 3D Architectures with Freeform Structures.

3D printing has become an important strategy for constructing graphene smart structures with arbitrary shapes and complexities. Compared with graphene oxide ink/gel/resin based manners, laser-induced graphene (LIG) is unique for facile and scalable assembly of 1D and 2D structures but still faces size and shape obstacles for constructing 3D macrostructures. In this work, a brand-new LIG based additive manufacturing (LIG-AM) protocol is developed to form bulk 3D graphene with freeform structures without introducing extra binders, templates, and catalysts. On the basis of selective laser sintering, LIG-AM creatively irradiates polyimide (PI) powder-bed for triggering both particle-sintering and graphene-converting processes layer-by-layer, which is unique for assembling varied types of graphene architectures including identical-section, variable-section, and graphene/PI hybrid structures. In addition to exploring combined graphitizing and fusing discipline, processing efficiency and assembling resolution of LIG-AM are also balanceable through synergistic control of lasing power and powder-feeding thickness. By further studying various process dependent properties, a LIG-AM enabled aircraft-wing section model is finally printed to comprehensively demonstrate its shiftable process, hybridizable structure, and multifunctional performance including force-sensing, anti-icing/deicing, and microwave shielding and absorption.

Small-Data-Driven Temporal Convolutional Capsule Network for Locomotion Mode Recognition of Robotic Prostheses.

Locomotion mode recognition has been shown to substantially contribute to the precise control of robotic lower-limb prostheses under different walking conditions. In this study, we proposed a temporal convolutional capsule network (TCCN) which integrates the spatial-temporal-based, dilation-convolution-based, dyna- mic routing and vector-based features for recognizing locomotion mode recognition with small data rather than big-data-based neural networks for robotic prostheses. TCCN proposed in this study has four characteristics, which extracts the (1) spatial-temporal information in the data and then makes (2) dilated convolution to deal with small data, and uses (3) dynamic routing, which produces some similarities to the human brain to process the data as a (4) vector, which is different from other scalar-based networks, such as convolutional neural network (CNN). By comparison with a traditional machine learning, e.g., support vector machine(SVM) and big-data-driven neural networks, e.g., CNN, recurrent neural network(RNN), temporal convolutional network(TCN) and capsule network(CN). The accuracy of TCCN is 4.1% higher than CNN under 5-fold cross-validation of three-locomotion-mode and 5.2% higher under the 5-fold cross-validation of five-locomotion modes. The main confusion we found appears in the transition state. The results indicate that TCCN may handle small data balancing global and local information which is closer to the way how the human brain works, and the capsule layer allows for better processing vector information and retains not only magnitude information, but also direction information.

Touchless interactive teaching of soft robots through flexible bimodal sensory interfaces.

In this paper, we propose a multimodal flexible sensory interface for interactively teaching soft robots to perform skilled locomotion using bare human hands. First, we develop a flexible bimodal smart skin (FBSS) based on triboelectric nanogenerator and liquid metal sensing that can perform simultaneous tactile and touchless sensing and distinguish these two modes in real time. With the FBSS, soft robots can react on their own to tactile and touchless stimuli. We then propose a distance control method that enabled humans to teach soft robots movements via bare hand-eye coordination. The results showed that participants can effectively teach a self-reacting soft continuum manipulator complex motions in three-dimensional space through a "shifting sensors and teaching" method within just a few minutes. The soft manipulator can repeat the human-taught motions and replay them at different speeds. Finally, we demonstrate that humans can easily teach the soft manipulator to complete specific tasks such as completing a pen-and-paper maze, taking a throat swab, and crossing a barrier to grasp an object. We envision that this user-friendly, non-programmable teaching method based on flexible multimodal sensory interfaces could broadly expand the domains in which humans interact with and utilize soft robots.

Biodegradable-Glass-Fiber Reinforced Hydrogel Composite with Enhanced Mechanical Performance and Cell Proliferation for Potential Cartilage Repair.

Polyvinyl alcohol (PVA) hydrogels are promising implants due to the similarity of their low-friction behavior to that of cartilage tissue, and also due to their non-cytotoxicity. However, their poor mechanical resistance and insufficient durability restricts their application in this area. With the development of biodegradable glass fibers (BGF), which show desirable mechanical performance and bioactivity for orthopedic engineering, we designed a novel PVA hydrogel composite reinforced with biodegradable glass fibers, intended for use in artificial cartilage repair with its excellent cytocompatibility and long-term mechanical stability. Using structure characterization and thermal properties analysis, we found hydrogen bonding occurred among PVA molecular networks as well as in the PVA-BGF interface, which explained the increase in crystallinity and glass transition temperature, and was the reason for the improved mechanical performance and better anti-fatigue behavior of the composites in comparison with PVA. The compressive strength and modulus for the PBGF-15 composite reached 3.05 and 3.97 MPa, respectively, equaling the mechanical properties of human articular cartilage. Moreover, the increase in BGF content was found to support the proliferation of chondrocytes in vitro, whilst the PVA hydrogel matrix was able to control the ion concentration by adjusting the ions released from the BGF. Therefore, this novel biodegradable-glass-fiber-reinforced hydrogel composite possesses excellent properties for cartilage repair with potential in medical application.

Anti-Disturbance Sliding Mode Control of a Novel Variable Stiffness Actuator for the Rehabilitation of Neurologically Disabled Patients.

Lower limb exoskeletons are widely used for rehabilitation training of patients suffering from neurological disorders. To improve the human-robot interaction performance, series elastic actuators (SEAs) with low output impedance have been developed. However, the adaptability and control performance are limited by the constant spring stiffness used in current SEAs. In this study, a novel load-adaptive variable stiffness actuator (LaVSA) is used to design an ankle exoskeleton. To overcome the problems of the LaVSA with a larger mechanical gap and more complex dynamic model, a sliding mode controller based on a disturbance observer is proposed. During the interaction process, due to the passive joints at the load side of the ankle exoskeleton, the dynamic parameters on the load side of the ankle exoskeleton will change continuously. To avoid this problem, the designed controller treats it and the model error as a disturbance and observes it with the disturbance observer (DOB) in real time. The first-order derivative of the disturbance set is treated as a bounded value. Subsequently, the parameter adaptive law is used to find the upper bound of the observation error and make corresponding compensation in the control law. On these bases, a sliding mode controller based on a disturbance observer is designed, and Lyapunov stability analysis is given. Finally, simulation and experimental verification are performed. The wearing experiment shows that the resistance torque suffered by humans under human-robot interaction is lower than 120 Nmm, which confirms that the controller can realize zero-impedance control of the designed ankle exoskeleton.

3D-Laminated Graphene with Combined Laser Irradiation and Resin Infiltration toward Designable Macrostructure and Multifunction.

Macroscopic 3D graphene has become a significant topic for satisfying the continuously upgraded smart structures and devices. Compared with liquid assembling and catalytic templating methods, laser-induced graphene (LIG) is showing facile and scalable advantages but still faces limited sizes and geometries by using template induction or on-site lay-up strategies. In this work, a new LIG protocol is developed for facile stacking and shaping 3D LIG macrostructures by laminating layers of LIG papers (LIGPs) with combined resin infiltration and hot pressing. Specifically, the constructed 3D LIGP composites (LIGP-C) are compatible with large area, high thickness, and customizable flat or curved shapes. Additionally, systematic research is explored for investigating critical processing parameters on tuning its multifunctional properties. As the laminated layers are stacked from 1 to 10, it is discovered that piezoresistivity (i.e., gauge factor) of LIGP-C dramatically reflects an ≈3900% improvement from 0.39 to 15.7 while mechanical and electrical properties maintain simultaneously at the highest levels, attributed to the formation of densely packed fusion layers. Along with excellent durability for resisting multiple harsh environments, a sensor-array system with 5 × 5 LIGP-C elements is finally demonstrated on fiber-reinforced polymeric composites for accurate strain mapping.

Cantilever-based differential pressure sensor with a bio-inspired bristled configuration.

Inspired by the bristled wing configuration of tiny insects, we proposed a novel polyimide (PI) cantilever-based differential pressure (DP) sensor. This bristled PI cantilever with a thin metallic piezoresistor was designed to detect the pressure difference that induced the aerodynamic loading on the surface of the cantilever. Owing to the aerodynamic characteristics of the bristled cantilever, the DP-sensor with the bristled cantilever could not only retain a comparable sensitivity with that of the paddle cantilever under low differential pressures but also achieve a higher theoretical upper detection limit due to the enhanced leakage of the bristles. Experimental results indicated that the DP-sensor with bristled cantilevers extended the detection range by ∼30% in comparison with the DP-sensor with paddle cantilevers. The high sensitivity, wide detection range, and facile fabrication process of these bio-inspired DP-sensors make them promising for future applications.

Tensegrity metamaterials for soft robotics.

3D-printed flexible tensegrities with metamaterial properties enable customizable complex locomotion in soft robots.

Design optimization and experimental study of a novel mechanism for a hover-able bionic flapping-wing micro air vehicle.

Allomyrina dichotomahas a natural ultra-high flying ability and maneuverability. Especially its ability to fly flexibly in the air, makes it more adaptable to the harsh ecological environment. In this study, a bionic flapping-wing micro air vehicle (FMAV) is designed and fabricated by mimicking the flight mode ofA. dichotoma. Parametric design was employed for combining the airframe structure and flight characteristics analysis. To improve the transmission efficiency and compactness of the FMAV mechanisms, this study first analyses the body structure ofA. dichotoma, and then proposes a novel mechanism of FMAV based on its biological motion characteristics, the flight motion characteristics, and its musculoskeletal system. By optimizing the flapping-wing mechanism and mimicking the flying mechanism ofA. dichotoma, the large angle amplitude and the high-frequency flapping motion can be achieved to generate more aerodynamic force. Meanwhile, to improve the bionic effect and the wing performance of FMAV, the flexible deformation ofA. dichotomawings for each flapping period was observed by a high-speed camera. Furthermore, the bionic design of wings the prototype was carried out, therefore the wings can generate a high lift force in the flapping process. The experiment demonstrated that the aircraft can achieve a flapping angle of 160 degrees and 30 Hz flapping frequency. The attitude change of FMAV is realized by mimicking the movement for the change of attitude of theA. dichotoma, by changing the angle of attack of the wing, and executing the flight action of multiple degrees of freedom including pitch, roll and yaw. Finally, the aerodynamic experiment demonstrated that the prototype can offer 27.8 g lift and enough torque for altitude adjustment.

Parametric generation of three-dimensional gait for robot-assisted rehabilitation.

For robot-assisted rehabilitation and assessment of patients with motor dysfunction, the parametric generation of their normal gait as the input for the robot is essential to match with the features of the patient to a greater extent. In addition, the gait needs to be in three-dimensional space, which meets the physiological structure of the human better, rather than only on a sagittal plane. Thus, a method for the parametric generation of three-dimensional gait based on the influence of the motion parameters and structure parameters is presented. First, the three-dimensional gait kinematic of participants is collected, and trajectories of ankle joint angle and ankle center position are calculated. Second, for the trajectories, gait features are extracted including gait events indicating the physiological features of walking gait, in addition to extremes indicating the geometrical features of the trajectories. Third, regression models are derived after using leave-one-out cross-validation for model optimization. Finally, cubic splines are fitted between the predicted gait features to generate the trajectories for a full gait cycle. It is inferred that the generated curves match the measured curves well. The method presented herein gives an important reference for research into lower limb rehabilitation robots.

Knee exoskeleton enhanced with artificial intelligence to provide assistance-as-needed.

Robotic therapy is a useful method applied during rehabilitation of stroke patients (to regain motor functions). To ensure active participation of the patient, assistance-as-needed is provided during robotic training. However, most existing studies are based on a predetermined desired trajectory, which significantly limits the use of this method for more complex scenarios. In this paper, artificial intelligence (AI) agents are introduced to enhance the robot so that a knee exoskeleton can be autonomously controlled. A new assist-as-needed (AAN) method is proposed, where the subjects and agents cooperatively control movements. An electromyographic (EMG)-controlled knee exoskeleton with an interesting screen game is developed. Two different AI agents, modular pipeline and deep Q-network, are introduced; both can control the exoskeleton to play the screen game independently. The human-robot cooperative control is studied with two different assistant strategies, i.e., fixed assistant ratio and AAN. Eight healthy subjects participated in the initial experiment, and four assistant modes were studied. The game scores obtained by the two agents were significantly higher than those obtained by healthy subjects (EMG control), indicating that using the agents to assist stroke rehabilitation is possible. The AAN method demonstrated a better performance than the fixed assistant ratio method, indicated by the higher integral muscle activation level and participant score. Compared to a fully active control (EMG control) and fully fixed guidance (AI control), human-robot cooperative control had significantly higher integral muscle activation levels, i.e., the subjects were more involved and motivated during training. Using AI agents to power rehabilitation robots is a promising way to realize AAN rehabilitation.