Reducing the resistance of vehicles, ships, aircraft and other means of transport during movement can significantly improve the speed, save energy and reduce emissions. After billions of years of continuous evolution, organisms in nature have gradually developed the ability to move at high speed to achieve better survival. These evolved organisms provide a perfect template for the human development of drag reduction materials. Revealing the unique physiological structural characteristics of organisms and their relationship with resistance during movement can provide a feasible approach tosolving the problem of reducing friction resistance. Whether flying in the sky, running on the ground, swimming in the water, or even living in the soil, many creatures in various environments have the ability to reduce resistance. Driven by these inspirations, researchers have done a lot of work to explore and imitate these biological epidermis structures to achieve drag reduction. In this paper, the biomimetic drag reduction materials is introduced in detail in the order of drag reduction mechanism, structural characteristics of biological epidermis (including marine animals, flying animals, soil animals and plants), biomimetic preparation methods, performance testing methods and application fields. Finally, the potential of various biomimetic drag reduction materials in engineering application and the problems to be overcome are summarized and prospected. This paper can help readers comprehensively understand the research progress of biomimetic drag reduction materials, and provide reference for further designing the next generation of drag reduction materials.

Annelid-inspired robots exhibit excellent motion adaptability and structural compliance, enabling them to navigate con-lfined, hazardous, or complex environments such as pipelines, soil, or the gastrointestinal tract. This review summarizes key developments in their bionic part design, actuation methods, material selection, and performance characteristics.　Comparative analyses show that different actuation strategies (e.g., pneumatic, shape memory alloys, and electroactive polymers, ete.) need to be weighed in terms of their advantages, limitations, and applicable environments. Materials likesilicone rubber and SMA are evaluated for their strength, flexibility, and energy performance. Quantitative benchmarks of velocity, load capacity, and energy consumption are presented to highlight design-performance correlations. Prospective research directions include the integration of multifunctional adaptive materials, real-time feedback sensing systems, and scalable architectures for autonomous operation in unstructured environments.

This review article presents a comprehensive overview of emerging technologies in bone tissue engineering (BTE). This rapidly advancing field addresses the challenges of bone defects and injuries beyond traditional treatments like autografts and allografts. The study highlights the integration of 3D bioprinting, stem cell therapy, gene therapy, biomaterials, nanotechnology, and computational modeling as transformative approaches in BTE. Developing biomimetic scaffolds, advanced bio-inks, and composite nanomaterials has enhanced seaffold design, improving mechanical properties and biocompatibility. Innovatiohs in gene therapy and bioactive molecule delivery are showcased for their ability to modulate cellular behavior and enhance osteogenesis. Stem cell-based therapies leverage the regenerative potential of mesenchymal stem cells, facilitating tissue integration and functional restoration. Computational tools, including finite element analysis　(FEA) and agent-based modelling, aid in the optimization of scaffold design, predicting mechanical responses and biological behaviors. Despite notable progress, signifieant challenges, such as achieving reliable vascularization, sealable manu-facturing of engineered constructs, and effective clinical translation, remain substantial barriers to widespread adoption.　Future research efforts focused on refining these technologies are vital for translating innovative strategies into elinical practice, paving the way for personalized regenerative solutions in bone repair.

Medical implant from different materials such as metals, ceramics, polymers and composites have gained a lot of research attraction due to wide applications in medical industry for treatment, surgical operations and preparing artificial body parts. In this work, we highlight a comprehensive review of medical implant mechanism, various types of implant materials, factors affecting the performance of implant and different characterization techniques. This review provides an overall summary of the state-of-the-art progress on various interesting and promising material-based medical implant. Finally, few new prospects are explained from the established theoretical and experimental results for real-life applications. This study is expected to promote extended interest of scientists and engineers in recent trend of modern biomaterials based medical implant.

Peri-implant mucositis is the mucosal inflammatory lesion around implants that does not result in the loss of the peri-implant bone that supports them. Furthermore, Peri-implantitis (PI), a medical condition affecting the tissues surrounding dental implants, is characterized by inflammation and a progressive loss of supporting bone. Of the several types of Nanoparticles (NPs), a lot of research has been done on the effects of Metal NPs (MNPs)—such as those made of silver, zinc, and copper—and non-MNPs—such as those made of Graphene Oxide (GO), Carbon-based NPs (CNPs), and Chitosan (CS) NPs—on peri-implant microorganisms. These NPs serve as antibacterial and anti-inflammatory agents and cover dental implants. Furthermore, Peri-implant Disease (PID) and many others in the oral and dental domains may be effectively treated using Green Synthesis (GS) NPs enabled by various biological sources. Compared to chemical and physical processes, GS offers several benefits, including non-toxicity, pollution-free production, environmental friendliness, cost-effectiveness, and sustainability. Hence, the significance of GS NPs, both MNPs and non-MNPs, was first explored in this work. Using eco-friendly methods, we then reviewed the PID-related effects of various MNPs and non-MNPs synthesized. NPs, both MNPs and non-MNPs, have great potential as a future therapy for PI, and the environmentally friendly manufacturing process may play a significant role in this development. Consequently, we have looked into the benefits and drawbacks of this treatment method in terms of clinical practice in our study. Research from reputable sources, such as PubMed and Google Scholar, was used to compile the papers included in the review article. Researchers may make progress in producing MNPs and non-MNPs NPs for treating PI by adopting GS.

Autonomous legged robots, capable of navigating uneven terrain, can perform a diverse array of tasks. However, designing locomotion controllers remains challenging. In particular, designing a controller based on durable and reliable proprioceptive sensors, is essential for achieving adaptability. Presently, the controller must either be manually designed for specific robots and tasks, or developed using machine-learning techniques, which require extensive training time and result in complex controllers. Inspired by animal locomotion, we propose a simple yet comprehensive closed-loop modular framework that utilizes minimal proprioceptive feedback (i.e., the Coxa–Femur (CF) joint angle), enabling a quadruped robot to efficiently navigate unpredictable and uneven terrains, including the step and slope. The framework comprises a basic neural control network capable of rapidly learning optimized motor patterns, and a straightforward module for sensory feedback sharing and integration. In a series of experiments, we show that integrating sensory feedback into the base neural control network aids the robot in continually learning robust motor patterns on flat, step, and slope terrain, compared with the open-loop base framework. Sharing sensory feedback information across the four legs enables a quadruped robot to proactively navigate unpredictable steps with minimal interaction. Furthermore, the controller remains functional even in the absence of sensor signals. This control configuration was successfully transferred to a physical robot without any modifications.

The stiffness information of the grasped object at the initial contact stage can be effectively used to adjust the grasping force of the prosthetic hand, thereby preventing damage to the object. However, the object’s deformation and contact force are often minimal during the initial stage and not easily obtained directly. Additionally, stiffness estimation methods for prosthetic hands often require contact sensors, which can easily lead to poor contact issues. To address the above issues, this paper proposes the model-based stiffness estimation of grasped objects for underactuated prosthetic hands without force sensors. First, the kinematic model is linearized at the contact points to achieve the estimation of the linkage angles in the underactuated prosthetic hand. Secondly, the motor parameters are estimated using the Kalman filter method, and the grasping force is obtained from the dynamic model of the underactuated prosthetic hand. Finally, the contact model of the prosthetic hand grasping an object is established, and an online stiffness estimation method based on the contact model for the grasped object is proposed using the iterative reweighted least squares method. Experimental results show that this method can estimate the stiffness of grasped objects within 250 ms without contact sensors.

This article reviews recent advancements, innovative strategies, and the key challenges in Drug Delivery Systems (DDS)　for bone regeneration, focusing on tissue engineering. It highlights the limitations of current surgical interventions forbone regeneration, particularly autogenic bone grafts, and discusses the exploration of alternative materials and methods, including allogeneic and xenogeneic bone grafts, synthetic materials, and biodegradable polymers. The objective is to provide a comprehensive understanding of how contemporary DDS can be optimized and integrated with tissue engineering approaches for more effective bone regeneration therapies. The review explained the mechanisms through which DDS enhance bone repair processes, identifies critical factors influencing their efficacy and safety, and offers an overview of current trends and future perspectives in the field. It emphasizes the need for advanced strategies in bone regeneration that focus on precise control of DDS to address bone conditions such as osteoporosis, trauma, and genetic predispositions leading to fractures.

Wall climbing robots can be used to undertake missions in many unstructured environments. However, current wall climbing robots have mobility difficulties such as in the turning or accelarating. One of the main reasons for the limitations is the poor flexibility of the spines. Soft robotic technology can actively enable structure deformation and stiffness varations, which provides a solution for the design of active flexible spines. This research utilizes pneumatic soft actuators to design a flexible spine with the abilities of actively bending and twisting by each joint. Using bending and torsion moment equilibriums, respectively, from air pressure to material deformations, the bending and twisting models for a single actuator with respect to different pressure are obtained. The theoretical models are verified by finite-element method simulations and experimental tests. In addition, the bending and twisiting motions of single joint and whole spine are analytically modeled. The results show that the bionic spine can perform desired deformations in accordance with the applied pressure on specified chambers. The variations of the stiffness are also numerically assessed. Finally, the effectiveness of the bionic flexible spine for actively producing sequenced motions as biological spine is experimentally validated. This work demonstrated that the peneumatic spine is potential to improve the spine flexibility of wall climbing robot.

Birds have developed near-perfect structures and functionality over millions of years of natural evolution. To improve the efficiency of fixed-wing vehicles in different environments, researchers have developed deformable wings inspired by the wing structures of birds. Shape Memory Alloy (SMA) is applied as a smart material to the deformable wing. Compared with other drive methods, SMA actuators have the advantages of high drive capacity and a simple structure for driving wing deformation. According to the shape memory effect, SMA actuators are classified as single-range and dual-range actuators. The wing structure designed for each SMA drive is unique. By comparing and analyzing the structures of airfoils, airfoils with similar drive forms and deformation structures are put together for review and discussion. The deformable wings are categorized into out-of-face deformation, in-face deformation, airfoil curvature deformation, and combined deformation with multiple degrees of freedom based on the structure and location of the wing that produces the deformation. An overview of the deformed wing is introduced by telling the bionic theory of seagulls. The principles of deformation of the wing, the mechanics of the SMA actuator mechanism, and the aerodynamic characteristics of the deformable wing are presented. The structure and working principle of SMA actuators for each type of deformable wing are explained in detail. Methods and approaches to study the deformability of deformable wings are analyzed and summarized. This work provides comprehensive insights and perspectives for future studies of SMA-driven deformable airfoils.

Tensegrity structures, embodying the principles of continuous tensioning and discrete compression, have emerged as fundamental frameworks in locomotive soft robotics for navigating uneven and unpredictable environments, owing to their flexible and resilient traits. By means of a straightforward and cost-effective method to achieve structure-driven, vibration-driven tensegrity shows great potential, particularly in tasks demanding random exploration. However, the design guidance for vibration-driven tensegrity and their performance evaluation in unstructured terrain remain unrevealed due to the complex dynamics of the structure. This paper presents a small six-bar tensegrity robot, driven by wireless vibration motors, designed for deployment in disaster rescue and search scenarios. Finite element simulation is used to investigate how structural characteristics, excitation parameters, and the arrangement of motors affect the kinematic performance of this tensegrity system. A prototype of the six-bar tensegrity robot with three motors located on the lower ends of the three lower struts is designed and manufactured after the numerical simulations. A simple control policy which adjusts the motion of the tensegrity robot by turning on or off the motors on different locations is proposed. The prototype with and without the control policy is tested in man-made environments of various complexity. It shows that the ability and efficiency of the tensegrity robot in exploring unstructured environments is significantly enhanced by the proposed control policy. It is believed that the potential of the vibration-driven tensegrity robot could be further exploited by integrating multi-source sensors and more intelligent control policies.

Detecting and distinguishing infrared radiation for non-invasive medical diagnostic purposes has been attempted for basic surface temperature assessment since the middle of the 20th century. However, the long wavelength and low energy of infrared radiation impede the detection of signals from deeper tissue layers, significantly limiting its use in diagnostics. To overcome these limitations, a novel approach was developed by combining a semiconductor gallium arsenide chip and prism-based optics that enabled the detection of signals in the infrared and terahertz spectrum. Challenges related to penetration depth and thermal noises were addressed by neural network modelling.

Antennae are significant chemosensory and mechanosensory organs for insects and need careful maintenance. Bees use a pair of comb-like tools located on the forelimbs to brush and remove contaminants from their antennae. We filmed antenna grooming in three different bee species and observed that all bees raise their heads while grooming their antennae. We conducted a study to examine the effects of the distinctive grooming apparatus, as well as the antenna’s material and structural characteristics, on grooming behavior in both free-head and constrained-head scenarios. Head-raising increases the grooming speed by 300% compared to the situation where the head is constrained. It allows the bees to scrape the antennae 5 times per second. In addition, we proposed a mechanical model based on the morphological data to determine that raising the head increases the contact force by 50%. These findings will facilitate the development of innovative approaches for cleaning extended structures featuring bristly surfaces.

This article presents the design of a microfabricated bio-inspired flapping-wing Nnano Aaerial Vvehicle (NAV), driven by an electromagnetic system. Our approach is based on artificial wings composed of rigid bodies connected by compliant links, which optimise aerodynamic forces though replicating the complex wing kinematics of insects. The originality of this article lies in a new design methodology based on a triple equivalence between a 3D model, a multibody model, and a mass/spring model (0D) which reduces the number of parameters in the problem. This approach facilitates NAV optimisation by using only the mass/spring model, thereby simplifying the design process while maintaining high accuracy. Two wing geometries are studied and optimised in this article to produce large-amplitude wing motions (approximately 40^\circ ), and enabling flapping and twisting motion in quadrature. The results are validated thanks to experimental measurements for the large amplitude and through finite element simulations for the combined motion, confirming the effectiveness of this strategy for a NAV weighing less than 40 mg with a wingspan of under 3 cm.

Throughout the previous studies, none of them are involved in analysing the downwash flow effect on the control surface of the Flapping Wing Rotor (FWR). An overset CFD numerical model is built up and validated to study the downwash flow’s effect on the stability of the FWR. After simulation, a cone like self-lock region which acts as the critical condition determining the stability of FWR is found. Only when the flow’s resultant velocity acting on the control surface lies in the stable region, the FWR can keep stable. The size of the cone like self-lock stable region can be enlarged by increasing the maximum feasible deflection angle constrained by mechanical design or enhancing the equivalent downwash flow velocity. Among all the simulated cases, when J?=?2.67 (f=5 Hz, \dot {\psi }=5 r/s), the largest average equivalent downwash flow velocities are found. On the other hand, the recovery torque could be enhanced due to the increase of the arm of the lateral force. According to these simulation results, a 43 g FWR model with two control surfaces and two stabilizers is then designed. A series of flight tests is then conducted to help confirm the conclusion of the mechanism research in this work. Overall, this study points out several strategies to increase the flight stability of the FWR and finally realizes the stable climb flight and mild descent flight of the FWR.

This paper presents a novel rehabilitation robot designed to address the challenges of Passive Range of Motion (PROM) exercises for frozen shoulder patients by integrating advanced scapulohumeral rhythm stabilization. Frozen shoulder is characterized by limited glenohumeral motion and disrupted scapulohumeral rhythm, with therapist-assisted interventions being highly effective for restoring normal shoulder function. While existing robotic solutions replicate natural shoulder biomechanics, they lack the ability to stabilize compensatory movements, such as shoulder shrugging, which are critical for effective rehabilitation. Our proposed device features a 6 Degrees of Freedom (DoF) mechanism, including 5 DoF for shoulder motion and an innovative 1 DoF Joint press for scapular stabilization. The robot employs a personalized two-phase operation: recording normal shoulder movement patterns from the unaffected side and applying them to guide the affected side. Experimental results demonstrated the robot’s ability to replicate recorded motion patterns with high precision, with Root Mean Square Error (RMSE) values consistently below 1 degree. In simulated frozen shoulder conditions, the robot effectively suppressed scapular elevation, delaying the onset of compensatory movements and guiding the affected shoulder to move more closely in alignment with normal shoulder motion, particularly during arm elevation movements such as abduction and flexion. These findings confirm the robot’s potential as a rehabilitation tool capable of automating PROM exercises while correcting compensatory movements. The system provides a foundation for advanced, personalized rehabilitation for patients with frozen shoulders.

Bamboo is an important building material with natural hygroscopicity, and the mechanism of water effects on its deformation and fracture behavior has not been fully revealed. For this purpose, a novel in-situ testing method was developed in this study, which coupled Acoustic Emission (AE) and Digital Image Correlation (DIC) techniques. This method was used to investigate the effects of various Moisture Content (MC) levels (0, 6%, 15%, and 25%) on the tensile behavior of bamboo. The results showed that as the MC increased from 0 to 25%, the tensile strength of bamboo decreased from 163 to 110 MPa, the Young's modulus dropped from 8.5 to 3.9 GPa, and the elongation increased from 4.3 to 14%. An increase in MC could effectively promote the occurrence of subcritical cracks and micro-interfacial dissociations in bamboo. The synergistic effect of these two factors facilitated strain dispersion, ensuring adaptability to large deformations. Additionally, it was found that an increase in MC could significantly alter the fracture mode. This ingenious synergistic effect in bamboo was revealed for the first time in this study. The mechanisms discovered in this study may provide some important insights into the design and fabrication of advanced biomimetic heterostructures and biomimetic interfacial materials.

Tree knots are generally considered defects in wood, but how the surrounding structures of the defects affects strength of wood has not been studied. Here the mechanical properties of static compression and hole bearing tests were designed for encased knots and intergrown knots, and the strengthening mechanism of streamline tissue and connecting interface was analyzed by finite element modeling. And the two reinforced structures were applied to composite structural holes and connecting holes, which significantly improved open hole compressive strength and hole bearing strength. And the finite element models for two kinds of composite hole were created to analyze how the stress field around the reinforced structure strengthens the composite. Both the experimental results and the finite analysis results show that the streamline structure could effectively improve the compressive properties of composite structural holes, and the connecting interface provided a stable constraint for giving full play to the hole bearing properties of stronger materials. These two structures will provide reference for the structural design of lightweight composites.

Locomotion performance degradation after carrying payloads is a significant challenge for insect-scale microrobots. Previously, a legged microrobot named BHMbot with a high load-carrying capacity based on front-leg actuation configuration and efficient running gait was proposed. However, insects, mammals and reptiles in nature typically use their powerful rear legs to achieve rapid running gaits for predation or risk evasion. In this work, the load-carrying capacity of the BHMbots with front-leg actuation and rear-leg actuation configurations is comparatively studied. Simulations based on a dynamic model with four degrees of freedom, along with experiments, have been conducted to analyze the locomotion characteristics of the two configurations under different payload masses. Both simulation and experimental results indicate that the load-carrying capacity of the microrobots is closely related to their actuation configurations, which leads to different dynamic responses of the microrobots after carrying varying payload masses. For microrobots with body lengths of 15 mm, the rear-leg actuation configuration exhibits a 31.2% enhancement in running speed compared to the front-leg actuation configuration when unloaded. Conversely, when carrying payloads exceeding 5.7 times the body mass (350 mg), the rear-leg actuation configuration demonstrates an 80.1% reduction in running speed relative to the front-leg actuation configuration under the same payload conditions.

In recent years, sEMG (surface electromyography) signals have been increasingly used to operate wearable devices. The development of mechanical lower limbs or exoskeletons controlled by the nervous system requires greater accuracy in recognizing lower limb activity. There is less research on devices to assist the human body in uphill movements. However, developing controllers that can accurately predict and control human upward movements in real-time requires the employment of appropriate signal pre-processing methods and prediction algorithms. For this purpose, this paper investigates the effects of various sEMG pre-processing methods and algorithms on the prediction results. This investigation involved ten subjects (five males and five females) with normal knee joints. The relevant data of the subjects were collected on a constructed ramp. To obtain feature values that reflect the gait characteristics, an improved PCA algorithm based on the kernel method is proposed for dimensionality reduction to remove redundant information. Then, a new model (CNN?+?LSTM) was proposed to predict the knee joint angle. Multiple approaches were utilized to validate the superiority of the improved PCA method and CNN-LSTM model. The feasibility of the method was verified by analyzing the gait prediction results of different subjects. Overall, the prediction time of the method was 25 ms, and the prediction error was 1.34?±?0.25 deg. By comparing with traditional machine learning methods such as BP (backpropagation) neural network, RF (random forest), and SVR (support vector machine), the improved PCA algorithm processed data performed the best in terms of convergence time and prediction accuracy in CNN-LSTM model. The experimental results demonstrate that the proposed method (improved PCA?+?CNN-LSTM) effectively recognizes lower limb activity from sEMG signals. For the same data input, the EMG signal processed using the improved PCA method performed better in terms of prediction results. This is the first step toward myoelectric control of aided exoskeleton robots using discrete decoding. The study results will lead to the future development of neuro-controlled mechanical exoskeletons that will allow troops or disabled individuals to engage in a greater variety of activities.

Lower extremity robotic exoskeletons (LEEX) can not only improve the ability of the human body but also provide healing treatment for people with lower extremity dysfunction. There are a wide range of application needs and development prospects in the military, industry, medical treatment, consumption and other fields, which has aroused widespread concern in society. This paper attempts to review LEEX technical development. First, the history of LEEX is briefly traced. Second, based on existing research, LEEX is classified according to auxiliary body parts, structural forms, functions and fields, and typical LEEX prototypes and products are introduced. Then, the latest key technologies are analyzed and summarized, and the research contents, such as bionic structure and driving characteristics, human–robot interaction (HRI) and intent-awareness, intelligent control strategy, and evaluation method of power-assisted walking efficiency, are described in detail. Finally, existing LEEX problems and challenges are analyzed, a future development trend is proposed, and a multidisciplinary development direction of the key technology is provided.

Natural organisms have different techniques to avoid enemies, such as chameleon skin with innate camouflage ability to change with the surrounding environment. Inspired by this, a microfluidic biomimetic chameleon skin based on infrared (IR) information processing is proposed for active thermal camouflage in a dynamic infrared background. Microfluidic circulation in microcavities distributed under the skin is controlled by a thermal camouflage system. The structure and working principle of the biomimetic skin are introduced, and the thermal camouflage system is established and tested to explore the heat transfer characteristics between the skin and the fluid. The mechanism of collecting the background infrared information and regulating the skin temperature through the control signal generated by the infrared information processing system is illustrated. Furthermore, the dynamic thermal response of the skin is tested when transitioning between different temperature backgrounds, modeling the ambient temperature of the sand, woodland and lakes where chameleons live. The performance of the skin is evaluated by measuring the camouflage responding time of the skin to an external heat source. The results show that the chameleon biomimetic skin is naturally transitioned and matched by infrared information processing and microfluidics. The limitation that the conventional thermal camouflage technology cannot adapt to the dynamic combat environment is overcome and the weaknesses of a small camouflage band range and a single form of camouflage are resolved in this study, thus effectively improving the target’s survivability in combat.

Freely shuttling in complex terrain is a basic skill of multi-legged animals. To make the hexapod robot have omnidirectional motion ability by controlling only one parameter, this paper uses the motion control method based on Central Pattern Generator (CPG), maps the output signal of CPG to the foot end trajectory space of the hexapod robot, and proposes an omnidirectional gait controller strategy. In addition, to enable the hexapod robot to adapt to unstructured terrain, an adaptive method based on Dynamic Threshold (DT) is proposed to enable the hexapod robot move in all directions without changing the heading angle in unstructured terrain. Finally, the feasibility of the proposed method is verified by virtual simulation and hexapod robot prototype experiment. Results show that the hexapod robot can omnidirectional motion without changing the heading angle and has good stability in unstructured terrain.

Whale optimization algorithm (WOA) tends to fall into the local optimum and fails to converge quickly in solving complex problems. To address the shortcomings, an improved WOA (QGBWOA) is proposed in this work. First, quasi-opposition-based learning is introduced to enhance the ability of WOA to search for optimal solutions. Second, a Gaussian barebone mechanism is embedded to promote diversity and expand the scope of the solution space in WOA. To verify the advantages of QGBWOA, comparison experiments between QGBWOA and its comparison peers were carried out on CEC 2014 with dimensions 10, 30, 50, and 100 and on CEC 2020 test with dimension 30. Furthermore, the performance results were tested using Wilcoxon signed-rank (WS), Friedman test, and post hoc statistical tests for statistical analysis. Convergence accuracy and speed are remarkably improved, as shown by experimental results. Finally, feature selection and multi-threshold image segmentation applications are demonstrated to validate the ability of QGBWOA to solve complex real-world problems. QGBWOA proves its superiority over compared algorithms in feature selection and multi-threshold image segmentation by performing several evaluation metrics.

Pulmonary Hypertension (PH) is a global health problem that affects about 1% of the global population. Animal models of PH play a vital role in unraveling the pathophysiological mechanisms of the disease. The present study proposes a Kernel Extreme Learning Machine (KELM) model based on an improved Whale Optimization Algorithm (WOA) for predicting PH mouse models. The experimental results showed that the selected blood indicators, including Haemoglobin (HGB), Hematocrit (HCT), Mean, Platelet Volume (MPV), Platelet distribution width (PDW), and Platelet–Large Cell Ratio (P-LCR), were essential for identifying PH mouse models using the feature selection method proposed in this paper. Remarkably, the method achieved 100.0% accuracy and 100.0% specificity in classification, demonstrating that our method has great potential to be used for evaluating and identifying mouse PH models.

Variable Stiffness Actuation (VSA) is an efficient, safe, and robust actuation technology for bionic robotic joints that have emerged in recent decades. By introducing a variable stiffness elastomer in the actuation system, the mechanical-electric energy conversion between the motor and the load could be adjusted on-demand, thereby improving the performance of the actuator, such as the peak power reduction, energy saving, bionic actuation, etc. At present, the VSA technology has achieved fruitful research results in designing the actuator mechanism and the stiffness adjustment servo, which has been widely applied in articulated robots, exoskeletons, prostheses, etc. However, how to optimally control the stiffness of VSAs in different application scenarios for better actuator performance is still challenging, where there is still a lack of unified cognition and viewpoints. Therefore, from the perspective of optimal VSA performance, this paper first introduces some typical structural design and servo control techniques of common VSAs and then explains the methods and applications of the Optimal Variable Stiffness Control (OVSC) approaches by theoretically introducing different types of OVSC mathematical models and summarizing OVSC methods with varying optimization goals and application scenarios or cases. In addition, the current research challenges of OVSC methods and possible innovative insights are also presented and discussed in-depth to facilitate the future development of VSA control.

With the growing demand for miniaturized workspaces, the demand for microrobots has been increasing in robotics research. Compared to traditional rigid robots, soft robots have better robustness and safety. With a flexible structure, soft robots can undergo large deformations and achieve a variety of motion states. Researchers are working to design and fabricate flexible robots based on biomimetic principles, using magnetic fields for cable-free actuation. In this study, we propose an inchworm-shaped soft robot driven by a magnetic field. First, a robot is designed and fabricated and force analysis is performed. Then, factors affecting the soft robot’s motion speed are examined, including the spacing between the magnets and the strength and frequency of the magnetic field. On this basis, the motion characteristics of the robot in different shapes are explored, and its motion modes such as climbing are experimentally investigated. The results show that the motion of the robot can be controlled in a two-dimensional plane, and its movement speed can be controlled by adjusting the strength of the magnetic field and other factors. Our proposed soft robot is expected to find extensive applications in various fields.

As the torso is critical to the coordinated movement and flexibility of vertebrates, a 6-(Degree of Freedom) DOF bionic parallel torso with noteworthy motion space was designed in our previous work. To improve the compliance of the parallel mechanism, a pair of virtual muscle models is constructed on both sides of the rotating joints of each link of the mechanism, and a bionic muscle control algorithm is introduced. By analyzing the control parameters of the muscle model, dynamic characteristics similar to those of biological muscle are obtained. An adaptive stiffness control is proposed to adaptively adjust the stiffness coefficient with the change in the external load of the parallel mechanism. The attitude closed-loop control can effectively keep the attitude angle unchanged when the position of the moving platform changes. The simulations and experiments are undertaken to validate compliant movements and the flexibility and adaptability of the parallel mechanism.

The vast diversity of morphologies, body size, and lifestyles of snakes represents an important source of information that can be used to derive bio-inspired robots through a biology-push and pull process. An understanding of the detailed kinematics of swimming snakes is a fundamental prerequisite to conceive and design bio-inspired aquatic snake robots. However, only limited information is available on the kinematics of swimming snake. Fast and accurate methods are needed to fill this knowledge gap. In the present paper, three existing methods were compared to test their capacity to characterize the kinematics of swimming snakes. (1) Marker tracking (Deftac), (2) Markerless pose estimation (DeepLabCut), and (3) Motion capture were considered. (4) We also designed and tested an automatic video processing method. All methods provided different albeit complementary data sets; they also involved different technical issues in terms of experimental conditions, snake manipulation, or processing resources. Marker tracking provided accurate data that can be used to calibrate other methods. Motion capture posed technical difficulties but can provide limited 3D data. Markerless pose estimation required deep learning (thus time) but was efficient to extract the data under various experimental conditions. Finally, automatic video processing was particularly efficient to extract a wide range of data useful for both biology and robotics but required a specific experimental setting.

Flapping-Wing Micro-Air Vehicles are likely to suffer from airflow perturbations. They can mimic the wing modulation of insects in airflow perturbations. However, our knowledge of wing modulation of insects to airflow perturbations remains limited. Here, we subjected hoverflies to headwind and lateral gust perturbations and filmed their wing motions. Then, computational fluid dynamics was employed to estimate the effects of hoverflies’ wing kinematic modulations. We also clipped off the antennae of hoverflies to test whether the wing kinematic modulations were different. Results show that hoverflies increase the mean positional angle and modulate the deviation angle to make the wing tip paths of upstroke and downstroke close to compensate for the pitch moment perturbations in the headwind gust. Hoverflies employ asymmetric responses in positional angle in the lateral gust. The stroke amplitude of the left (right) wing increases (decreases) and the mean positional angle of the left (right) wing decreases (increases) during the right lateral gust. Antennae have little effect on the wing kinematic modulations in the lateral gust. These asymmetric responses produce a roll moment, tilting the body to resist the side force generated by the gust. This is a typical helicopter model employed by hoverflies to alleviate the gust. These results provide insight into the remarkable capacity of hoverflies to contend with gusts and can also inspire the design of flapping-wing micro-air vehicles.

In this paper, a bionic mantis shrimp amphibious soft robot based on a dielectric elastomer is proposed to realize highly adaptive underwater multimodal motion. Under the action of an independent actuator, it is not only able to complete forward/backwards motion on land but also has the ability of cyclically controllable transition motion from land to water surface, from water surface to water bottom and from water bottom to land. The fastest speed of the soft robot on land is 170 mm/s, and it can crawl while carrying up to 4.6 times its own weight. The maximum speeds on the water surface and the water bottom are 30 mm/s and 14.4 mm/s, respectively. Furthermore, the soft robot can climb from the water bottom with a 9° slope transition to land. Compared with other similar soft robots, this soft robot has outstanding advantages, such as agile speed, large load-carrying capacity, strong body flexibility, multiple motion modes and strong underwater adaptability. Finally, nonlinear motion models of land crawling and water swimming are proposed to improve the environmental adaptability under multiple modalities, and the correctness of the theoretical model is verified by experiments.

On the base of controllable variable stiffness property, variable stiffness composites were the main components of functional materials in aerospace. However, the relatively low mechanical strength, stiffness range, and response rate restricted the application of variable stiffness composite. In this work, the novel variable stiffness composite system with characteristics of repeatable high load bearing and response rate was successfully prepared via the double-layer anisotropic structure to solve the bottlenecks of variable stiffness composites. The novel variable stiffness composite systems were composed of variable stiffness layer of polycaprolactone (PCL) and the driven layer of silicone elastomer with alcohol, which continuously changed Young’s modulus from 0.1 to 7.263 MPa (72.63 times variation) in 200 s and maintained maximum weight of 11.52 times its own weight (8.5 g). Attributed to the relatively high variable stiffness range and load bearing value of variable stiffness composite system, the repeatable response process led to the efficient high load driven as “muscle” and diversified precise grab of objects with different shapes as “gripper”, owning widespread application prospects in the field of bionics.

Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and adaptability. Although soft in-pipe robots have great improvements in flexibility, they still have manufacturing difficulties due to their reliance on high-performance soft materials. Tensegrity structure is a kind of self-stressed spatial structure consisting discrete rigid struts connected by a continuous net of tensional flexible strings, which combines the advantages of both rigid structures and soft structures. By applying tensegrity structures into robotics, this paper proposes a novel worm-like tensegrity robot for moving inside pipes. First, a robot module capable of body deformation is designed based on the concept of tensegrity and its deformation performance is analyzed. Then, the optimal parameters of the module are obtained based on the tensegrity form-finding. The deformation ability of the tensegrity module is tested experimentally. Finally, the worm-like tensegrity robot that can crawl inside pipes is developed by connecting three modules in series. Motion performance and load capacity are tested on the prototype of the worm-like tensegrity robot by experiments of moving in horizontal pipe, vertical pipe, and elbow pipe. Experimental results demonstrate the effectiveness of the proposed design and suggest that the robot has high compliance, mobility, and adaptability although with simple structure and low cost.

This paper uses the Butterfly Optimization Algorithm (BOA) with dominated sorting and crowding distance mechanisms to solve multi-objective optimization problems. There is also an improvement to the original version of BOA to alleviate its drawbacks before extending it into a multi-objective version. Due to better coverage and a well-distributed Pareto front, non-dominant rankings are applied to the modified BOA using the crowding distance strategy. Seven benchmark functions and eight real-world problems have been used to test the performance of multi-objective non-dominated advanced BOA (MONSBOA), including unconstrained, constrained, and real-world design multiple-objective, highly nonlinear constraint problems. Various performance metrics, such as Generational Distance (GD), Inverted Generational Distance (IGD), Maximum Spread (MS), and Spacing (S), have been used for performance comparison. It is demonstrated that the new MONSBOA algorithm is better than the compared algorithms in more than 80% occasions in solving problems with a variety of linear, nonlinear, continuous, and discrete characteristics based on the Pareto front when compared quantitatively. From all the analysis, it may be concluded that the suggested MONSBOA is capable of producing high-quality Pareto fronts with very competitive results with rapid convergence.

There are many theories behind the colors of a bird’s feathers. Many of these theories point to the color’s purpose to attract mates and hide from predators. Some recent investigations concluded that the dark colors of birds help in reducing the drag force during flight. A new theory is presented in the current research, which states that a bird's dark color not only reduces the drag, but the color pattern also improves the overall flight performance, and each color pattern has a different type of flight performance improvement. This difference in improvement is a result of variation in hot and cold surfaces on the bird skin as a result of the variation between light and dark feather colors. To prove this new theory, thermal images were captured of real bird wings under the effect of infrared waves. Also, a novel wind tunnel wing with the ability to adjust the temperature in desired locations and patterns on the wing’s surface was manufactured and tested to evaluate the effect of aerodynamics forces as a function in the surface temperature and the hot–cold regions. The collected data from this wing showed potential flight efficiency improvements of 20%, comparing the lift-to-drag ratio for specific heating cases, which could increase the flight range. Individually considering lift and drag, there were specific heating cases with corresponding angles of attack in which these parameters improved by up to 20% and 7%, respectively. Some heating cases could increase the lift at a low angle of attack, which is helpful in cruise flight performance, while some cases could increase the maximum lift coefficient by 6%. This is very helpful in lowering stall and the minimum flight speeds. Furthermore, some cases could increase the lift-to-drag ratio, which led to an increase in the flight range. To better understand the effect of the various patterns, computational fluid dynamics (CFD) simulations were conducted on the wing. The new theory was proved based on the CFD results and verified through the successful results from the wind tunnel experiments.

Thunniform swimmers (tuna) have a swinging narrow sequence stalk and a moon-shaped tail fin, which performs poorly at slow speed, higher acceleration and turning maneuverability. In most cases, faster speed and higher maneuverability are mutually rejection for most marine creatures and their robotic opponents. This paper presents a novel hybrid tuna-like swimming robot for aquaculture water quality monitoring, which interleaves faster speed and higher maneuverability. The robotic prototype emphasizes on streamlining and enhanced maneuverability mechanism designs in conjunction with a narrow caudal propeller to the tail. The innovative design endows the robot to easily execute the multi-mode swimming gait, including forward swimming, turning, diving/surfacing. The capabilities of our robot are validated through a series of indoor swimming pool and field breeding ponds. The robotic fish can achieve a maximum speed up to about 1.16 m/s and a minimum turning radius less than 0.46 Body Lengths (BL) and its maximum turning speed can reach 78.6 °°/s. Due to its high speed, maneuverability and relatively small size, the robotic fish shed light on intelligent monitoring in complex aquatic environments.

There are many interesting flocking phenomena in nature, such as joint predation and group migration, and the intrinsic communication patterns of flocking are essential for studying group behavior. Traditional models of communication such as the pigeon flock model and the wolf pack model define all agents within a perceptual distance as the neighborhoods, and some models have fixed communicating numbers. There is a significant impact on the quality of the flocking formation when encountering poor initial state of the flocking, multiple obstacles, or loss of certain agents. To solve this problem, this paper proposes a local communication model with nearest agents in four directions. Based on this model and behavioral method, two distributed flocking formation algorithms are designed in this paper for different scenarios, namely the flocking algorithm and the circular formation algorithm. Numerical simulation results show that the flocking can pass through the obstacle area and re-formation smoothly, and also the formation quality of the flocking is better compared with the traditional communication model.

To solve the wall-wetting problem in internal combustion engines, the physical and chemical etching methods are used to prepare different wettability surfaces with various microstructures. The evaporation characteristics and morphological evolution processes of diesel and n-butanol droplets after hitting the various surfaces are investigated. The results show that the surface microstructures increase the surface roughness (Ra), enhancing the oleophilic property of the oleophilic surfaces. Compared with n-butanol droplets, the same surface shows stronger oleophobicity to diesel droplets. When a droplet hits an oleophilic property surface with a lower temperature, the stronger the oleophilicity, the shorter the evaporation time. For oleophilic surfaces, larger Ra leads to a higher Leidenfrost temperature (TLeid?Leid). The low TLeid?Leid caused by enhanced oleophobicity, dense microstructures and increased convex dome height facilitates droplet rebound and promotes the evaporation of the wall-impinging droplets into the cylinder. The evaporation rate of the droplets is not only related to the characteristics of the solid surfaces and the fuel droplets but also affected by the heat transfer rate to the droplets in different boiling regimes. The spreading diameter of a droplet on an oleophobic surface varies significantly less with time than that on an oleophilic surface under the same surface temperature.

The poor wear resistance and bio-inertness surface of polyetheretherketone (PEEK) limits the implant applications of PEEK and its composites. Carbon fiber (CFR) was used to boost the wear resistance of PEEK; however, the bioactivity of carbon fiber-reinforced polyetheretherketone (CFR-PEEK) composites is even worse. The bioactivity of CFR-PEEK can be enhanced by constructing 3D porous structure. Nevertheless, large number of sulfur component introduced by sulfonation shows cytotoxicity and can cause damage to human cells. Besides, the sulfur component affects the cytotoxicity and bioactivity of sulfonated CFR-PEEK (SCFR-PEEK). Hydrothermal treatment can sweep away the sulfur component in the 3D porous structure of SCFR-PEEK. Meanwhile, the changes in crystallinity and hardness after hydrothermal treatment may also affect the wear resistance. Therefore, the effect of hydrothermal temperature on wear resistance, cytotoxicity and bioactivity of SCFR-PEEK were studied. In this work, the samples with hydrothermal temperature 90–120 ℃ exhibited high wear resistance. The 3D pore structure of SCFR-PEEK unchanged after hydrothermal treatment, and the sulfur component in the 3D pore structure gradually decreased with increasing hydrothermal temperature by SEM images and EDS analysis. In addition, SCFR-PEEK treated in 90–120 ℃. Exhibited low cytotoxicity and high bioactivity, which is beneficial for the implant materials.

Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs. In such cases, head movements can be used as an alternative communication channel. In this study, a human–machine interface which is controlled by human head movements is designed and implemented. The proposed system enables users to steer the desired movement direction and to control the speed of an output device by using head movements. Head movements of the users are detected using a 6 DOF IMUs measuring three-axis accelerometer and three-axis gyroscope. The head movement axes and the Euler angles have been associated with movement direction and speed, respectively. To ensure driving safety, the speed of the system is determined by considering the speed requested by the user and the obstacle distance on the route. In this context, fuzzy logic algorithm is employed for closed-loop speed control according to distance sensors and reference speed data. A car model was used as the output device on the machine interface. However, the wireless communication between human and machine interfaces provides to adapt this system to any remote device or systems. The implemented system was tested by five subjects. Performance of the system was evaluated in terms of task completion times and feedback from the subjects about their experience with the system. Results indicate that the proposed system is easy to use; and the control capability and usage speed increase with user experience. The control speed is improved with the increase in user experience.