Biomimetics, Volume 10, Issue 5 (May 2025) – 27 articles

Continuum robots (CRs) are highly effective in grasping moving targets in space through whole-arm grasping (WAG), offering broad applicability and reliable capture. These characteristics make CRs particularly suitable for capturing non-cooperative space targets. Compliant control plays a crucial role in ensuring safe and reliable interactions during the grasping process. This paper proposes a virtual-integrated admittance control (VIAC) method specifically designed to enhance WAG by CRs. By proactively adjusting the robot’s trajectory before contact, the VIAC method effectively reduces the contact force exerted on the target during grasping, enabling compliant capture while preventing target escape and minimizing potential damage. This study first develops a mathematical model of the CR and addresses the inverse dynamics problem. Subsequently, the VIAC method is introduced to regulate contact force and improve grasping performance. This approach integrates virtual forces, derived from position information, with actual contact forces acting on the robot’s links, facilitating trajectory replanning through an admittance controller. The virtual forces, constructed based on improved virtual potential fields, reduce the relative velocities of robot links with respect to the target during the approach, ensuring successful grasping. Simulation results validate the effectiveness of the VIAC method, demonstrating a significant reduction in contact force compared to conventional admittance control. Full article

This paper proposes a learning-based joint morphing and flight control framework for avian-inspired morphing aircraft. Firstly, a novel multi-objective multi-phase optimal control problem is formulated to synthesize the comprehensive flight missions, incorporating additional requirements such as fuel consumption, maneuverability, and agility of the morphing aircraft. Subsequently, an auxiliary problem, employing $ϵ$-constraint and augmented state methods, is introduced to yield a finite and locally Lipschitz continuous value function, which facilitates the construction of a neural network controller. Furthermore, a multi-phase pseudospectral method is derived to discretize the auxiliary problem and formulate the corresponding nonlinear programming problem, where open loop optimal solutions of the multi-task flight mission are generated. Finally, a learning-based feedback controller is established using data from the open loop solutions, where a temporal masked attention mechanism is developed to extract information from sequential data more efficiently. Simulation results demonstrate that the designed attention module in the learning scheme yields a significant 53.5% reduction in test loss compared to the baseline model. Additionally, the proposed learning-based joint morphing and flight controller achieves a 37.6% improvement in average tracking performance over the fixed wing configuration, while also satisfying performance requirements for fuel consumption, maneuverability, and agility. Full article

Zeroing neural networks (ZNN), as a specialized class of bio-Iinspired neural networks, emulate the adaptive mechanisms of biological systems, allowing for continuous adjustments in response to external variations. Compared to traditional numerical methods and common neural networks (such as gradient-based and recurrent neural networks), this adaptive capability enables the ZNN to rapidly and accurately solve time-varying problems. By leveraging dynamic zeroing error functions, the ZNN exhibits distinct advantages in addressing complex time-varying challenges, including matrix inversion, nonlinear equation solving, and quadratic optimization. This paper provides a comprehensive review of the evolution of ZNN model formulations, with a particular focus on single-integral and double-integral structures. Additionally, we systematically examine existing nonlinear activation functions, which play a crucial role in determining the convergence speed and noise robustness of ZNN models. Finally, we explore the diverse applications of ZNN models across various domains, including robot path planning, motion control, multi-agent coordination, and chaotic system regulation. Full article

Soft modular biomimetic robots, driven by flexible actuators, are extensively used in various fields due to their excellent flexibility, environmental adaptability, and isomorphism. However, existing flexible modules typically possess no more than two degrees of freedom for structural limitations. In this study, a three-degree-of-freedom biomimetic segment driven by water hydraulic artificial muscles (WHAMs) and supported by springs was proposed, achieving integrated and modular design. The continuum robot composed of this segment can execute earthworm-, snake-, and elephant trunk-biomimetic motion modes based on operational environmental constraints. During long-distance operational tasks, distinct segments of the continuum robot can adopt varying biomimetic configurations to meet specific requirements. The closed-loop control characteristic tests were conducted on a single segment to evaluate its motion characteristics. The isomorphic master controller was designed based on the motion range of a single segment, with the maximum bending angle deviation between the master controller and biomimetic segment not exceeding 4°, and the system demonstrating favorable stability. Full article

A vole foraging-inspired dynamic path-planning method considering slippery road conditions is proposed for wheeled humanoid robots. Glazed and oily roads create a high risk of slipping for wheeled humanoid robots and hinder the realization of high-speed movement. But in a dynamic environment, road conditions such as material, texture, and attachments vary uncertainly in both space and time, and cannot be processed as quickly and easily as moving obstacles. Inspired by the process of voles searching for food, to address this challenge, a slip-risk-assessment method based on time–space decoupling is designed and integrated into a grid-based environmental model. On this basis, the dynamic path-planning model is constructed by combining the cost functions and constraints based on the slip-risk information. A two-level non-periodic cyclical dynamic planning mechanism is proposed based on conditional triggering. It adaptively and cyclically calls the global planning algorithm and the local re-planning algorithm according to the characteristics of environmental changes to autonomously avoid high-slip-risk areas and moving obstacles in real time. The experimental results show the effectiveness and practicality of the proposed planning method. Full article

Nanoparticles introduced into biological environments rapidly acquire a coating of biomolecules, forming a biocorona that dictates their biological fate. Among these biomolecules, proteins play a key role, but their interaction with nanoparticles during the adsorption process often leads to unfolding and functional loss. Evidence suggests that protein denaturation within the biocorona alters cellular recognition, signaling pathways, and immune responses, with significant implications for nanomedicine and nanotoxicology. This review explores the dynamic nature of the protein corona, emphasizing the influence of the local biological milieu on its stability. We synthesize findings from studies examining the physicochemical properties of nanoparticles—such as surface charge, hydrophobicity, and curvature—that contribute to protein structural perturbations. Understanding the factors governing protein stability on nanoparticle surfaces is essential for designing nanomaterials with improved targeting, biocompatibility, and controlled biological interactions. This review underscores the importance of preserving protein conformational integrity in the development of nanoparticles for biomedical applications. Full article

Imitating nature’s mechanisms has enormous potential to improve our lives and tools. Biomimetics emulates nature’s proven patterns and strategies to develop novel solutions widely applied in various fields. This study aims to propose an overall perspective and research direction for innovation using biomimetics. Using text network analysis and topic modeling, we analyzed the evolution of 5202 Korean R&D projects in biomimetics. The results indicate significant interdisciplinary collaborations between bioengineering, drug development, polymer chemistry, and robotics. Moreover, biomimetic national R&D has primarily focused on fundamental research and its trends reveal interconnection with topic clusters around intelligent robotics, biomedical engineering, and materials science. This study provides guidelines for governments and R&D organizations to establish biomimetic R&D plans and select convergence topics for innovation. Full article

The maximum k-coverage problem (MKCP) is a problem of finding a solution that includes the maximum number of covered rows by selecting k columns from an m $\times$n matrix of 0s and 1s. This is an NP-hard problem that is difficult to solve in a realistic time; therefore, it cannot be solved with a general deterministic algorithm. In this study, genetic algorithms (GAs), an evolutionary arithmetic technique, were used to solve the MKCP. Genetic algorithms (GAs) are meta-heuristic algorithms that create an initial solution group, select two parent solutions from the solution group, apply crossover and repair operations, and replace the generated offspring with the previous parent solution to move to the next generation. Here, to solve the MKCP with binary and integer encoding, genetic algorithms were designed with various crossover and repair operators, and the results of the proposed algorithms were demonstrated using benchmark data from the OR-library. The performances of the GAs with various crossover and repair operators were also compared for each encoding type through experiments. In binary encoding, the combination of uniform crossover and random repair improved the average objective value by up to 3.24% compared to one-point crossover and random repair across the tested instances. The conservative repair method was not suitable for binary encoding compared to the random repair method. In contrast, in integer encoding, the combination of uniform crossover and conservative repair achieved up to 4.47% better average performance than one-point crossover and conservative repair. The conservative repair method was less suitable with one-point crossover operators than the random repair method, but, with uniform crossover, was better. Full article

Research on clean production in automotive painting processes is a core component of achieving green manufacturing, addressing environmental regulatory challenges, and advancing sustainable development in the automotive industry by reducing volatile organic compound (VOC) emissions, optimizing resource utilization, and minimizing energy consumption. To reduce pollutants generated by automotive painting processes and improve coating efficiency, this study proposes a clean production method for automotive body painting based on an improved whale optimization algorithm from the perspective of “low-carbon consumption and emission-reduced production”. A multi-level, multi-objective decision-making model is developed by integrating three dimensions of clean production: material flow (optimizing material costs), energy flow (minimizing painting energy consumption), and environmental emission flow (reducing carbon emissions and processing time). The whale optimization algorithm is enhanced through three key modifications: the incorporation of nonlinear convergence factors, elite opposition-based learning, and dynamic parameter self-adaptation, which are then applied to optimize the automotive painting model. Experimental validation using the painting processes of TJ Corporation’s New Energy Vehicles (NEVs) demonstrates the superiority of the proposed algorithm over the MHWOA, WOA-RBF, and WOA-VMD. Results show that the method achieves a 42.1% increase in coating production efficiency, over 98% exhaust gas purification rate, 18.2% average energy-saving improvement, and 17.9% reduction in manufacturing costs. This green transformation of low-carbon emission-reduction infrastructure in painting processes delivers significant economic and social benefits, positioning it as a sustainable solution for the automotive industry. Full article

This review synthesizes current research on hydrofoil-propelled robots inspired by the swimming mechanisms of sea turtles and penguins. It begins by summarizing the swimming kinematics of these organisms, highlighting their superior aquatic performance as the primary motivation for biomimetic design. Next, established analytical methods for characterizing hydrofoil locomotion patterns are presented, along with a clear delineation of the decoupled motion components exhibited by sea turtle flippers and penguin wings. Such decoupling provides a systematic framework for guiding the design of driving mechanisms. Building on this biomechanical foundation, the review critically examines recent advances in biomimetic flexible hydrofoils that enhance propulsion efficiency through three synergistic mechanisms to enhance thrust generation, while identifying key challenges in material durability and non-linear fluid–structure interactions. The review then surveys existing hydrofoil actuation systems, which commonly reproduce coupled motions with multiple degrees of freedom (DOFs). Finally, representative biomimetic robots are examined: sea turtle-inspired forelimbs typically incorporate three DOFs, whereas penguin-inspired wings usually offer two DOFs. By aligning robotic designs with the decoupled motion patterns of the source organisms, this review offers critical insights to advance the development of hydrofoil propulsion systems for enhanced aquatic performance. Full article

The application of exoskeleton robots has demonstrated promising effectiveness in promoting the recovery of motor skills in patients with upper limb dysfunction. However, the joint misalignment caused by rigid exoskeletons usually leads to an uncomfortable experience for users. In this work, an adaptive cable-driven elbow exoskeleton inspired by the structural characteristics of the shrimp shell was developed to facilitate the rehabilitation of the elbow joint and to provide more compliant human-exoskeleton interactions. The exoskeleton was specifically designed for elbow flexion and extension, with a total weight of approximately 0.6 kg. Based on the mechanical design and cable configuration of the exoskeleton, the kinematics and dynamics of driving cables were analyzed. Subsequently, a PID-based control strategy was designed with cable kinematics. To evaluate the practical performance of the proposed exoskeleton in elbow assistance, a prototype was established and experimented with six subjects. According to the experimental results, the measured elbow joint angle trajectory is generally consistent with the desired trajectory, with a mean position tracking accuracy of approximately 0.997, which supports motion stability in rehabilitation scenarios. Meanwhile, the collected sEMG values from biceps brachii and brachioradialis under the exoskeleton condition show a significant reduction in average muscle activation by 37.7% and 28.8%, respectively, compared to the condition without exoskeleton. Full article

With the recent development of advanced industries, in addition to simple abrasions, the demand for wound dressing is gradually increasing in fields such as diabetes care. Factors affecting wound healing include pH, temperature, genetic factors, stress, smoking, and obesity, and studies on these are also increasing. In addition, studies on hydrogels, electrospun nanofibers, foams, films, plant-based materials, chitosan, gelatin, 3D printing, and chemosensors for wound healing are also increasing. However, although there are many data related to wound healing, there are not many studies that have systematically divided them into structures, materials, and monitoring through a review of the literature. Therefore, based on various studies on wound healing, wound-healing materials were classified into structures (films, foams, gauzes, and electrospun nanofibers), chemical materials, nature-based materials, and monitoring sensors, and a literature review was conducted. Full article

Background: Complex hindfoot pathologies involving critical-sized bone defects of the talus are difficult to manage. The current management involves arthrodesis and bone grafting with the defective talus, which have limitations in restoring structural integrity and functional goals. The advancement of 3D-printed scaffolds has opened new avenues to address such complex hindfoot pathologies, which may potentially improve treatment outcomes. The addition of platelet-rich fibrin further enhances healing potential. Method: This is a retrospective study involving six patients with severe talar bone loss secondary to osteomyelitis or avascular necrosis, where 3D-printed scaffolds coated with PRF were implemented in salvage surgery performed from 2023 to 2024. We intended to investigate the clinical outcomes in terms of healing time and union rate. Additionally, we evaluated the degree of deformity corrections and the patients’ clinical outcomes. Results: This study reports six complex reconstructions which achieved CT-confirmed union after a mean duration of 20.2 weeks. All patients were able to ambulate with full weight bearing after an average duration of 23.3 weeks. The patients demonstrated improved radiological parameters, VAS scores from 7.5 ± 1.4 points to 2.3 ± 1.2, and functional scores in all domains for AOFAS, FFI and SF-36. Conclusion: This study demonstrates the benefits of PRF-coated 3D-printed scaffolds in managing complex hindfoot cases, especially in the presence of significant bony defects. This modality has the potential to achieve a good union rate, near-anatomical correction and good functional outcomes. Full article

The workshop is a crucial site for ensuring the smooth operation of production activities within an enterprise, playing a significant role in its long–term development. A well–designed workshop layout can reduce material–handling costs during production and enhance the overall efficiency of the enterprise. This paper establishes a mathematical model for the workshop layout problem, aiming to minimize logistics transportation costs and maximize non–logistics relationships. Using a real–world case study, the White Shark Optimizer (WSO) algorithm is applied to solve the model. The results show that the transportation distance of the layout scheme obtained by the WSO algorithm is reduced by 381 m, 82 m, and 56 m, respectively, compared with the original layout, the Genetic Algorithm (GA), and the Sparrow Search Algorithm (SSA), and the non–logical relationship is increased by 24.84% and 1.6%, respectively. The layout scheme obtained by using the WSO algorithm is more excellent and can effectively improve the production efficiency of enterprises. Full article

The heel pad, located under the calcaneus of the human foot, is a hidden treasure that has been subjected to harsh mechanical conditions such as impact, vibration, and cyclic loading. This has resulted in a unique compartment structure and material composition, endowed with advanced biomechanical functions including cushioning, vibration reduction, fatigue resistance, and touchdown stability, making it an ideal natural bionic prototype in the field of bionic materials. It has been shown that the highly specialized structure and material composition of the heel pad endows it with biomechanical properties such as hyperelasticity, viscoelasticity, and mechanical anisotropy. These complex biomechanical properties underpin its advanced functions. Although it is known that these properties interact with each other, the detailed influence mechanism remains unclear, which restricts its application as a bionic prototype in the field of bionic materials. Therefore, this study provides a comprehensive review of the structure, materials, biomechanical properties, and functions of the heel pad. It focuses on elucidating the relationships between the structure, materials, biomechanical properties, and functions of heel pads and proposes insights for the study of bionic materials using the heel pad as a bionic prototype. Finally, a research idea to analyze the advanced mechanical properties of heel pads by integrating sophisticated technologies is proposed, aiming to provide directions for further in-depth research on heel pads and inspiration for the innovative design of advanced bionic materials. Full article

In this paper, an Improved Manta Ray Foraging Optimization (IMRFO) algorithm is proposed to address the challenge of parameter tuning in traditional PID controllers for artillery stabilization systems. The proposed algorithm introduces chaotic mapping to optimize the initial population, enhancing the global search capability; additionally, a sigmoid function and Lévy flight-based dynamic adjustment strategy regulate the selection factor and step size, improving both convergence speed and optimization accuracy. Comparative experiments using five benchmark test functions demonstrate that the IMRFO algorithm outperforms five commonly used heuristic algorithms in four cases. The proposed algorithm is validated through co-simulation and physical platform experiments. Experimental results show that the proposed approach significantly improves control accuracy and response speed, offering an effective solution for optimizing complex nonlinear control systems. By introducing heuristic optimization algorithms for self-tuning artillery stabilization system parameters, this work provides a new approach to enhancing the intelligence and adaptability of modern artillery control. Full article

To improve the maneuverability and agility of jumping robots, a variety of steerable jumping mechanisms have been actively studied. The steering ability enables a robot to reach a particular target by altering its jumping direction. To make this possible, we propose a miniature steerable jumping robot based on froghopper’s jumping principle: Moment cancellation is achieved via synchronous leg rotation, and a predictable jumping direction is achieved through an almost zero stiffness femoro-tibial joint. To satisfy these working principles, the robot is designed to have a four-bar shaped body structure and wire-driven knee joints. The four-bar body always synchronizes the leg operation by mechanically coupling the two jumping legs, which enables the robot to cancel out the moments and finally reduce the needless body spin. The knee joints are actuated using wires, and the wires are kept loose to maintain joint stiffness almost zero during take-off. Accordingly, the jumping direction is successfully predicted to determine the initial posture of the tibia. As a result, the proposed robot can change the jumping direction from −20 degrees to 20 degrees while reducing needless body spin. Full article

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