Biomimetics

This study compares the effectiveness of three methods—Fréchet Distance, Dynamic Time Warping (DTW), and Convolutional Neural Networks (CNNs)—in detecting similarities and pattern recognition in time series. It proposes a Pattern-Driven Case Generator (PDCG) framework to automate the creation of labeled time series data for training CNN models, addressing the challenge of manual dataset curation. By injecting controlled noise and interpolating diverse shapes (e.g., W/M/nAn/vVv), a PDCG synthesizes realistic training data that enhances model robustness. Experimental results demonstrate that the CNN model, trained with 10,000 PDCG-generated cases, achieves 86–98% accuracy in pattern recognition, outperforming traditional methods (Fréchet and DTW) for complex, misaligned, and variable-length sequences. The PDCG-enhanced CNN’s scalability and adaptability improve with larger datasets, validating the PDCG’s efficacy in bridging simulation and real-world applications. Full article

With daily oil consumption approaching 100 million barrels, the global demand continues to generate significant quantities of oily wastewater during oil extraction, refining, and transportation, and the development of effective oil–water separation technologies has become crucial. However, membrane corrosion is a challenge under the harsh conditions involved. Here, we are inspired by the lotus leaf to create a corrosion-resistant and robust superhydrophobic membrane using a general spraying method. By using this spraying process to apply the Graphene@PDMS heptane dispersion onto the mesh substrate, we create a biomimetic corrosion-resistant and robust superhydrophobic stainless steel mesh (SSM). The modified SSM can still maintain superhydrophobic properties after soaking in a strong acidity solution (pH = 1), robust alkalinity solution (pH = 14), or NaCl solution (15 days), which demonstrates excellent chemical stability. Moreover, the modified SSM shows strong mechanical stability during ultrasonic treatment for 2 h. The superhydrophobic SSM can be used to separate various kinds of oils from water with high flux and separation efficiency. It shows a high flux of 27,400 L·m⁻²·h⁻¹ and high separation efficiency of 99.42% for soybean oil–water separation using 400-mesh SSM. The biomimetic modified SSM demonstrates great potential for oil–water separation under harsh conditions, which gives it promise as a candidate in practical applications of oil–water separation. Full article

The development of prosthetic limbs has benefited individuals who suffered amputations due to accidents or medical conditions. During the development of conventional prosthetics, several challenges have been observed regarding the functional limitations, the restricted degrees of freedom compared to an actual human limb, and the biocompatibility issues between the surface of the prosthetic limb and the human tissue or skin. These issues could result in mobility impairments due to failed mimicry of the actual stress distribution, causing discomfort, chronic pain, and tissue damage or possible infections. Especially in cases where underlying conditions exist, such as diabetes, possible trauma, or vascular disease, a failed adaptation of the prosthetic limb could lead to complete abandonment of the prosthetic part. To address these challenges, the insertion of topologically optimized parts with a biomimetic approach has allowed the optimization of the mimicry of the complex functionality behavior of the natural body parts, allowing the development of lightweight efficient anthropomorphic structures. This approach results in unified stress distribution, minimizing the practical limitations while also adding an aesthetic that aids in reducing any possible symptoms related to social anxiety and impaired social functioning. In this paper, the development of a novel anthropomorphic designed prosthetic foot with a novel Thermoplastic Polyurethane-based composite (TPU-Ground Tire Rubber 10 wt.%) was studied. The final designs contain advanced sustainable polymeric materials, gyroid lattice geometries, and Finite Element Analysis (FEA) for performance optimization. Initially, a static evaluation was conducted to replicate the phenomena at the standing process of a conventional replicated above-knee prosthetic. Furthermore, dynamic testing was conducted to assess the mechanical responses to high-intensity exercises (e.g., sprinting, jumping). The evaluation of the dynamic mechanical response of the prosthetic limb was compared to actual plantogram-derived foot pressure data during static phases (standing, light walking) and dynamic phenomena (sprinting, jumping) to address the optimal geometry and density, ensuring maximum compatibility. This innovative approach allows the development of tailored prosthetic limbs with optimal replication of the human motion patterns, resulting in improved patient outcomes and higher success rates. The proposed design presented hysteretic damping factor and energy absorption efficiency adequate for load handling of intense exercises (0.18 loss factor, 57% energy absorption efficiency) meaning that it is suitable for further research and possible upcycling. Full article

In real-world applications, many complex problems can be formulated as mathematical optimization challenges, and efficiently solving these problems is critical. Metaheuristic algorithms have proven highly effective in addressing a wide range of engineering issues. The differentiated creative search is a recently proposed evolution-based meta-heuristic algorithm with certain advantages. However, it also has limitations, including weakened population diversity, reduced search efficiency, and hindrance of comprehensive exploration of the solution space. To address the shortcomings of the DCS algorithm, this paper proposes a multi-strategy differentiated creative search (MSDCS) based on the collaborative development mechanism and population evaluation strategy. First, this paper proposes a collaborative development mechanism that organically integrates the estimation distribution algorithm and DCS to compensate for the shortcomings of the DCS algorithm’s insufficient exploration ability and its tendency to fall into local optimums through the guiding effect of dominant populations, and to improve the quality of the DCS algorithm’s search efficiency and solution at the same time. Secondly, a new population evaluation strategy is proposed to realize the coordinated transition between exploitation and exploration through the comprehensive evaluation of fitness and distance. Finally, a linear population size reduction strategy is incorporated into DCS, which significantly improves the overall performance of the algorithm by maintaining a large population size at the initial stage to enhance the exploration capability and extensive search of the solution space, and then gradually decreasing the population size at the later stage to enhance the exploitation capability. A series of validations was conducted on the CEC2018 test set, and the experimental results were analyzed using the Friedman test and Wilcoxon rank sum test. The results show the superior performance of MSDCS in terms of convergence speed, stability, and global optimization. In addition, MSDCS is successfully applied to several engineering constrained optimization problems. In all cases, MSDCS outperforms the basic DCS algorithm with fast convergence and strong robustness, emphasizing its superior efficacy in practical applications. Full article

Biomimicry is redefining the design, architecture, and construction industries by transforming biological principles into innovative solutions that optimize structural, energy, and environmental performance. This study identifies the organisms and natural systems that inspire the industry, establishing patterns, trends, and key applications. Through a systematic literature review, 70 studies documenting bio-inspired applications in materials, structures, and construction systems were analyzed. The findings are organized into a categorization of organisms based on their biological group and a detailed classification according to imitation criteria—form, function, structure, and process—highlighting their applications in the built environment. The results demonstrate the convergence between technology and nature, underscoring the potential of biomimicry for the development of a more sustainable and resilient industry. Furthermore, this study identifies the most recurring sources of inspiration and the main lines of interest in the implementation of biomimetic strategies in construction, consolidating its role as a key tool for the architecture of the future. Based on these findings, the research proposes a biomimetic design framework that aligns architectural needs with suitable imitation strategies and biological analogs, offering a practical tool to guide decision making in the early design phases. Full article

The accelerating population aging and increasing demand for higher work efficiency have made the research and the application of lower-limb assistive exoskeletons a primary focus in recent years. This paper reviews the research progress of lower-limb squat assistive wearable devices, with a focus on classification methods, research outcomes, and products from both domestic and international markets. It also analyzes the key technologies involved in their development, such as mechanical mechanisms, control strategies, motion sensing, and effectiveness validation. From an industrial design perspective, the paper also explores the future prospects of lower-limb squat assistive wearable devices in four key areas: multi-signal sensing, intelligent control, human–machine collaboration, and experimental validation. Finally, the paper discusses future development trends in this field. Full article

This paper explores a bio-inspired swarm confrontation algorithm specifically designed for complex hilly terrains in the context of electronic games. The novelty of the proposed algorithm lies in its utilization of biologically inspired strategies to facilitate adaptive and efficient decision-making in dynamic environments. Drawing from the collective hunting behaviors of various animal species, this paper distills two key confrontation strategies: focused fire for target selection and flanking encirclement for movement coordination and attack execution. These strategies are embedded into a decentralized swarm decision-making framework, enabling agents to exhibit enhanced responsiveness and coordination in complex gaming landscapes. To validate its effectiveness, extensive experiments were conducted, comparing the proposed approach against three established algorithms. The results demonstrate that this method achieves a confrontation win rate exceeding 80%, outperforming existing techniques in both engagement efficiency and survivability. Additionally, two novel performance indices, namely the average agent quantity loss rate and the average health loss rate, are introduced to provide a more comprehensive assessment of algorithmic effectiveness. Furthermore, the impact of key algorithmic parameters on performance indices is analyzed, offering insights into the adaptability and robustness of the proposed algorithm. Full article

The effect of corrugated wings on the aerodynamic characteristics of a dragonfly-like hovering flapping wing is investigated using two-dimensional numerical simulations. Two types of pitch motion profiles, namely ‘sinusoidal’ and ‘trapezoidal’, are employed. The results obtained from the corrugated wings at Reynolds number Re = 2150 are then compared with the flat plate geometries to analyze the aerodynamic benefits of wing corrugation. The aerodynamic characteristics of corrugated wings are investigated quantitatively using cycle-averaged vertical force coefficient. For the qualitative investigation, time histories of vertical force coefficient, vorticity, and surface pressure distribution are used. The results reveal that the corrugated wings perform better than the flat plates in all three flapping configurations for both sinusoidal and trapezoidal pitch profiles. For a tandem wing with a sinusoidal pitch profile, the corrugated wings yield a vertical force generation nearly 14%, 22%, and 12%, higher than the flat plate geometries for ψ = 0°, 90°, and 180°, respectively. The corrugated wing sheds a relatively stronger detached counter clockwise vortex (CCWV) on the lower surface as compared to the flat plate, and hence, the vertical force is much higher for the corrugated wing. For a tandem wing with a trapezoidal pitch profile, the corrugated wings yield a vertical force generation nearly 27%, 22%, and 57%, higher than the flat plate geometries for ψ = 0°, 90°, and 180°, respectively. In corrugated wing geometry, the delayed stall mechanism is slightly postponed due to the corrugation shape’s ability to trap the vortex structures, leading to a positive effect on vertical force production. Full article

In extreme weather conditions, the use of unmanned ground vehicles (UGVs) for material distribution enhances safety. We introduce a two-echelon unmanned ground vehicle routing problem (2E-UGVRP) and proposes a hybrid Artificial Bee Colony–Wild Horse Optimizer (HABC-WHO) algorithm to solve it. In this approach, the optimal solution obtained from the Artificial Bee Colony algorithm replaces the worst solution of the Wild Horse Optimizer. To further improve the algorithm’s performance, strategies such as large neighborhood search, two-optimization (2-Opt) operation, and satellite subpath crossover are incorporated. The algorithm’s effectiveness is demonstrated through the solution of 43 benchmark instances, with performance comparisons against a Genetic Algorithm (GA), Discrete Wild Horse Optimizer (DWHO), and Discrete Artificial Bee Colony–Fixed Neighborhood Search (DABC-FNS). The results clearly show the significant superiority of the proposed algorithm. Additionally, the algorithm is applied to material distribution by two-echelon UGVs under extreme weather conditions, yielding promising results. Experimental findings indicate that the algorithm exhibits strong solving capability and high precision. Full article

Human action recognition aims to understand human behavior and is crucial in enhancing the intelligence and naturalness of human–computer interaction and bionic robots. This paper proposes a method to improve the complexity and real-time performance of action recognition by combining the Kinect sensor with the OpenPose algorithm, the Levenberg–Marquardt (LM) algorithm, and the Dynamic Time Warping (DTW) algorithm. First, the Kinect V2 depth sensor is used to capture color images, depth images, and 3D skeletal point information from the human body. Next, the color image is processed using OpenPose to extract 2D skeletal point information, which is then mapped to the depth image to obtain 3D skeletal point information. Subsequently, the LM algorithm is employed to fuse the 3D skeletal point sequences with the sequences obtained from Kinect, generating stable 3D skeletal point sequences. Finally, the DTW algorithm is utilized to recognize complex movements. Experimental results across various scenes and actions demonstrate that the method is stable and accurate, achieving an average recognition rate of 95.94%. The method effectively addresses issues, such as jitter and self-occlusion, when Kinect collects skeletal points. The robustness and accuracy of the method make it highly suitable for application in robot interaction systems. Full article

This study numerically explores a bird-inspired tail-less unmanned aerial vehicle (UAV) design which can turn through proverse yaw by using a bell-shaped spanload wing configuration. The research methodology consists of two phases. In the first phase, the objective is to use computational fluid dynamics (CFD) simulations to validate that the bell-shaped spanload wing configuration produces proverse yaw, instead of adverse yaw, similar to other typical wing configurations. This allows the UAV to turn without a tail. The solver used is OpenFOAM and a special self-written routine is used to allow the grid to move together with the UAV, which has six degrees-of-freedom (6DOFs) to translate and rotate when its ailerons deflect after reaching steady motion. In the second phase, we investigate the effect of the sweep angle on the proverse yaw. Results show that proverse yaw is indeed produced due to the bell-shaped spanload wing configuration, as CFD simulation shows the UAV turning after aileron deflection. The effect of the sweep angle is more profound on the proverse yaw as simulations show that increasing the sweep angle by 10° increases the turning effect slightly, but decreasing it by 10° instead results in adverse yaw. These findings will have important implications for improving aircraft efficiencies and the development of wing designs. Full article

In this research, we propose a bagworm-inspired robot that can acquire its exterior by incorporating various objects from the surrounding environment into its skin. This study was inspired by the bagworm, the larva of the giant bagworm moth, which wraps itself around straw and other materials to use as a nest. When the robot is active outdoors, it is surrounded by natural materials such as sand, fallen leaves, and pieces of wood, and can change its skin by attaching or detaching these materials as needed. In the previous study, the authors developed a camouflage robot that assimilates with the outside world by incorporating natural environmental sand. In this study, by using a water-soluble adhesive as the adhesive material, it is possible to take in a larger number of external substances than before. We also conducted experiments with natural materials, including leaves and pebbles, and confirmed that the robot could pick them up. We expect that by developing these functions, robots will not only have camouflage capabilities but also the ability to reinforce their own skin like bagworms. Full article

Papilio polytes is a cosmopolitan Lepidoptera species of controversial use and management. It remained unclear how its epidermal ultrastructure changes during development and how this affects its wetting properties in relation to water and pesticide adjuvants. In this study, the epidermis of P. polytes was systematically examined at the important feeding stage (from 3rd to 5th instar). Its ultrastructure was quantitatively observed by scanning electron microscopy. Its wetting properties towards the three main types of adjuvants and water were evaluated by contact angle. The chemical functional group differences between different instars and different adjuvant treatments were analyzed by mid-infrared spectroscopy. The correlation between the ultrastructural deformation and variations in wetting properties was verified by simulation tests. It was found that the complication of the epidermal structure was the leading factor for the significant increase in hydrophobicity during development. Cationic adjuvants had the best infiltrating effect on complex epidermal structures and organosilicon adjuvants had the best infiltrating effect on simple epidermal structures. The results provide data for biomimetic design for different wetting properties and suggest the feasibility and advantages of selecting pesticide adjuvants based on developmental changes in the structural characteristics of the insect epidermis. Full article

Goats can walk freely and flexibly in complex environments such as concave and convex or soft ground. And their flexible spine has functions such as adjusting balance and providing auxiliary power during movement, while the limbs only have support functions. The spine has an adjustable and decisive role in the pressure on the sole of the hoof of the goat. Therefore, the goat spine was taken as the bionic prototype, the three-dimensional force distribution of the goat body space was analyzed, and the optimal spinal space curve was explored, combined with the goat gait cycle. Based on the study of spinal curve arrangement and placement, the spinal curve was stretched along the grouser length direction. The soil contact surface structure of the track monomer was constructed based on functional simulation. And the bionic structure of the track monomer with superior adhesion performance was explored. The results of simulation analysis and soil tank test both showed that the attachment performance of bionic structure was better than that of an ordinary structure. It showed that adding bionic curves to the contact surface of the track monomer could significantly improve the adhesion performance, and the bionic structure with a single bionic curve arranged on the complete contact surface of the track monomer had the best adhesion performance. Moreover, the adhesion of the optimal track monomer bionic structure was increased by 19.22 N compared with an ordinary structure in the soil tank test, which verified the superiority of the track monomer bionic structure design. It provides a new method and a new idea for improving the adhesion performance of tracked vehicle in hilly areas. Full article

Background/Objectives: This study evaluated the trueness and precision of three low-cost 3D printers compared to a professional-grade printer in fabricating orthodontic models. Methods: Two upper dental models, one crowded and one non-crowded, were designed using Blenderfordental and Autolign. The models were printed with Anycubic M3 Premium, Anycubic Photon D2, Phrozen Sonic Mini 8K, and Ackuretta Sol at 45° and 90° using Elegoo orthodontic and Ackuretta Curo resins. A total of 384 models were produced: 256 crowded (128 at 90° and 128 at 45°) and 128 non-crowded (all at 45°). Chitubox Dental Slicer and ALPHA AI slicer were used for slicing. Post-processing involved cleaning with Ackuretta Cleani and curing in Ackuretta Curie. The models were scanned with Smartoptics Vinyl Open Air. Trueness was assessed using RMS deviation analysis in CloudCompare and linear measurements. Results: One-way ANOVA showed significant differences in trueness among the printers at 45° (p < 0.001) and 90° (p < 0.001). The Ackuretta Sol (LCD) exhibited the highest trueness, with the lowest mean RMS values at 45° (0.095 ± 0.008 mm) and 90° (0.115 ± 0.010 mm). The Anycubic M3 Premium (LCD) had the lowest trueness, with RMS values at 45° (0.136 ± 0.015 mm) and 90° (0.149 ± 0.012 mm). The 45° build angle resulted in significantly better trueness than 90° (p < 0.001). In linear measurements, deviations exceeding 0.25 mm were observed only in the R1 distance, except for the Ackuretta SOL, which remained below this threshold. Conclusions: The professional-grade printer demonstrated the best performance overall. Printing at a 45° build angle resulted in improved accuracy. Despite differences among devices, all printers produced results within clinically acceptable limits for orthodontic use. Full article

Focusing on the difficulty of lubrication in the scavenging port area of a cylinder liner of an actual marine two-stroke diesel engine, the transportation of interface lubricating oil was studied. In this paper, a biomimetic fish scale texture composed of fan-shaped and arc-shaped curves is designed, and the numerical simulation model is established according to this texture. Through simulation research, the variation rules of pressure distribution, interfacial velocity, and outlet volume flow rate on the biomimetic fish scale texture surface at different velocities and temperatures are obtained. Moreover, the biomimetic fish scale texture is machined on the surface of a reciprocating friction pair by laser etching, and the oil transport speed of the interface is tested under different conditions. The results show that the existence of the biomimetic fish scale texture on the friction pair can effectively improve the pressure difference between interfaces during reciprocating motion. The pressure difference enhances the flow properties of interfacial lubricating oil, thereby improving its mass transport capacity. In addition, increasing the movement speed and oil temperature can increase the oil transport speed of interfacial lubricating oil. The results of the experiment suggest that, under continuous and discontinuous interface conditions, compared with a friction pair without texture, the improvement rate of the lubricating oil transport speed at the interface of the friction pair with the biomimetic fish scale texture can reach 40.7% and 69.1%, respectively. Full article

Airway mucus plays a critical role in respiratory health, with diseases such as cystic fibrosis (CF) being characterized by mucus that exhibits increased viscosity and altered viscoelasticity. In vitro models that emulate these properties are essential for understanding the impact of CF mucus on airway function and for the development of therapeutic strategies. This study characterizes a mucus mimic composed of xanthan gum and locust bean gum, which is designed to exhibit the rheological properties of CF mucus. Mucus concentrations ranging from 0.07% to 0.3% w/v were tested to simulate different states of bacterial infection in CF. Key rheological parameters, including yield stress, storage modulus, loss modulus, and viscosity, were measured using an HR2 rheometer with strain sweep, oscillation frequency, and flow ramp tests. The results show that increasing the concentration enhanced the mimic’s elasticity and yield stress, with values aligning with those reported for CF mucus in pathological states. These findings provide a quantitative framework for tuning the rheological properties of mucus in vitro, allowing for the simulation of CF mucus across a range of concentrations. This mucus mimic is cost-effective, readily cross-linked, and provides a foundation for future studies examining the mechanobiological effects of mucus yield stress on epithelial cell layers, particularly in the context of bacterial infections and airway disease modeling. Full article

Jumping is a fundamental capability for wheeled-bipedal robots (WBRs) navigating unstructured terrains, with jump height and stability serving as indicators of the robot’s environmental adaptability. However, existing trajectory planning methods demand high output capacity from the joints and fail to balance computational load with trajectory tracking performance. This limitation hinders most robots from experimental validation. To address these challenges, this study presents an optimized virtual model, trajectory planning strategy, and control method. These solutions enhance both the height and stability of jumps while ensuring real-time execution on physical robots. Firstly, inspired by the human jumping mechanism, a Nonlinear Wheel-Spring-Loaded Inverted Pendulum (NW-SLIP) model was originally proposed as the virtual model for trajectory planning. The jump height is increased by 3.4 times compared to the linear spring model. Then, cost functions are established based on this virtual model, and the trajectory for each stage is iteratively optimized using Quadratic Programming (QP) and a bisection method. This leads to a 21.5% increase in the maximum jump height while reducing the peak joint torque by 14% at the same height. This significantly eases execution and enhances the robot’s trajectory-tracking ability. Subsequently, a leg statics model is introduced alongside the kinematics model to map the relationship between the virtual model and joint space. This approach improves trajectory tracking performance while circumventing the intricate calculation of the dynamics model, thereby enhancing jump consistency and stability. Finally, the proposed trajectory planning and jump control method is validated through both simulations and real-world experiments, demonstrating its feasibility and effectiveness in practical robotic applications. Full article

Anomalies refer to data inconsistent with the overall trend of the dataset and may indicate an error or an unusual event. Time series prediction can detect anomalies that happen unexpectedly in critical situations during the usage of a system or a network. Detecting or predicting anomalies in the traditional way is time-consuming and error-prone. Accordingly, the automatic recognition of anomalies is applicable to reduce the cost of defects and will pave the way for companies to optimize their performance. This unsupervised technique is an efficient way of detecting abnormal samples during the fluctuations of time series. In this paper, an unsupervised deep network is proposed to predict temporal information. The correlations between the neighboring samples are acquired to construct a graph of neighboring fluctuations. The extricated features related to the temporal distribution of the time samples in the constructed graph representation are used to impose the Chebyshev graph convolution layers. The output is used to train an adversarial network for anomaly detection. A modification is performed for the generative adversarial network’s cost function to perfectly match our purpose. Thus, the proposed method is based on combining generative adversarial networks (GANs) and a Chebyshev graph, which has shown good results in various domains. Accordingly, the performance of the proposed fusion approach of a Chebyshev graph-based modified adversarial network (Cheb-MA) is evaluated on the Numenta dataset. The proposed model was evaluated based on various evaluation indices, including the average F1-score, and was able to reach a value of 82.09%, which is very promising compared to recent research. Full article