Biomimetics

20 pages, 7865 KiB

Open AccessArticle

Design and Performance of a Neurosurgery Assisting Device

by Karla Nayeli Silva-Garcés, Marco Ceccarelli, Matteo Russo and Christopher René Torres-SanMiguel

Biomimetics 2025, 10(6), 345; https://doi.org/10.3390/biomimetics10060345 - 23 May 2025

This paper presents a new design solution for a neurosurgery-assisting device (NeurADe) based on a 3-RPS parallel kinematic mechanism. The NeurADe design employs compact linear actuators to accurately insert a cannula into specific areas of the brain. The CAD design and assembly of [...] Read more.

This paper presents a new design solution for a neurosurgery-assisting device (NeurADe) based on a 3-RPS parallel kinematic mechanism. The NeurADe design employs compact linear actuators to accurately insert a cannula into specific areas of the brain. The CAD design and assembly of a prototype are discussed in this paper. The preliminary NeurADe prototype features 3D printed parts and incorporates mechanical and electrical components, which are designed for ease of use and lightweight functionality. For design validation and operational characterization, sensors measuring current, acceleration, and force data were utilized, and testing results are discussed to prove the feasibility of the proposed design. Full article

(This article belongs to the Special Issue Recent Advances in Bioinspired Robot and Intelligent Systems)

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20 pages, 1723 KiB

Open AccessReview

Cellulose-Based Nanofibers in Wound Dressing

by Abdul Razak Masoud, Zeinab Jabbari Velisdeh, Mohammad Jabed Perves Bappy, Gaurav Pandey, Elham Saberian and David K. Mills

Biomimetics 2025, 10(6), 344; https://doi.org/10.3390/biomimetics10060344 - 23 May 2025

Abstract

Wound dressings have a significant role in managing trauma-related injuries, chronic lacerations, as well as post-operative complications, by preventing infections and promoting tissue regeneration. Conventional methods using sutures and gauze often pose constraints in healing effectiveness and cost. Emerging materials, particularly cellulose-based nanofibers, [...] Read more.

Wound dressings have a significant role in managing trauma-related injuries, chronic lacerations, as well as post-operative complications, by preventing infections and promoting tissue regeneration. Conventional methods using sutures and gauze often pose constraints in healing effectiveness and cost. Emerging materials, particularly cellulose-based nanofibers, offer a favorable choice due to their biodegradability, biocompatibility, and structural similarity to the extracellular matrix. Cellulose, being an abundant, naturally available biopolymer, forms the basis for modern materials for wound dressing. It is a very resourceful material due to its capability to be processed into films, fibers, and membranes with tailored properties. Surface modification of cellulose membranes with nanoparticles or bioactive compounds assists in enhancing the antimicrobial properties and supports sustained drug release, essential in chronic wound infections. Electrospinning and other modern fabrication techniques allow for controlling the fiber morphology and drug-delivery characteristics. This review highlights the properties, fabrication techniques, surface functionalization, and biomedical applications of cellulose-based materials in wound care. With increasing demand for effective and cost-effective wound treatments, cellulose nanofibers stand out as a sustainable, multifunctional platform for cutting-edge wound dressings, offering improved healing, reduced scarring, and potential for amalgamation with several drug delivery and tissue engineering approaches. Full article

(This article belongs to the Special Issue Advances in Biomaterials, Biocomposites and Biopolymers 2025)

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64 pages, 16560 KiB

Open AccessArticle

Multi-Strategy-Assisted Hybrid Crayfish-Inspired Optimization Algorithm for Solving Real-World Problems

by Wenzhou Lin, Yinghao He, Gang Hu and Chunqiang Zhang

Biomimetics 2025, 10(5), 343; https://doi.org/10.3390/biomimetics10050343 - 21 May 2025

Abstract

In order to solve problems with the original crayfish optimization algorithm (COA), such as reduced diversity, local optimization, and insufficient convergence accuracy, a multi-strategy optimization algorithm for crayfish based on differential evolution, named the ICOA, is proposed. First, the elite chaotic difference strategy [...] Read more.

In order to solve problems with the original crayfish optimization algorithm (COA), such as reduced diversity, local optimization, and insufficient convergence accuracy, a multi-strategy optimization algorithm for crayfish based on differential evolution, named the ICOA, is proposed. First, the elite chaotic difference strategy is used for population initialization to generate a more uniform crayfish population and increase the quality and diversity of the population. Secondly, the differential evolution strategy and the dimensional variation strategy are introduced to improve the quality of the crayfish population before its iteration and to improve the accuracy of the optimal solution and the local search ability for crayfish at the same time. To enhance the updating approach to crayfish exploration, the Levy flight strategy is adopted. This strategy aims to improve the algorithm’s search range and local search capability, prevent premature convergence, and enhance population stability. Finally, the adaptive parameter strategy is introduced to improve the development stage of crayfish, so as to better balance the global search and local mining ability of the algorithm, and to further enhance the optimization ability of the algorithm, and the ability to jump out of the local optimal. In addition, a comparison with the original COA and two sets of optimization algorithms on the CEC2019, CEC2020, and CEC2022 test sets was verified by Wilcoxon rank sum test. The results show that the proposed ICOA has strong competition. At the same time, the performance of ICOA is tested against different high-performance algorithms on 6 engineering optimization examples, 30 high–low-dimension constraint problems and 2 large-scale NP problems. Numerical experiments results show that ICOA has superior performance on a range of engineering problems and exhibits excellent performance in solving complex optimization problems. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 3rd Edition)

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43 pages, 7583 KiB

Open AccessArticle

A Particle Swarm Optimization-Guided Ivy Algorithm for Global Optimization Problems

by Kaifan Zhang, Fujiang Yuan, Yang Jiang, Zebing Mao, Zihao Zuo and Yanhong Peng

Biomimetics 2025, 10(5), 342; https://doi.org/10.3390/biomimetics10050342 - 21 May 2025

Abstract

In recent years, metaheuristic algorithms have garnered significant attention for their efficiency in solving complex optimization problems. However, their performance critically depends on maintaining a balance between global exploration and local exploitation; a deficiency in either can result in premature convergence to local [...] Read more.

In recent years, metaheuristic algorithms have garnered significant attention for their efficiency in solving complex optimization problems. However, their performance critically depends on maintaining a balance between global exploration and local exploitation; a deficiency in either can result in premature convergence to local optima or low convergence efficiency. To address this challenge, this paper proposes an enhanced ivy algorithm guided by a particle swarm optimization (PSO) mechanism, referred to as IVYPSO. This hybrid approach integrates PSO’s velocity update strategy for global searches with the ivy algorithm’s growth strategy for local exploitation and introduces an ivy-inspired variable to intensify random perturbations. These enhancements collectively improve the algorithm’s ability to escape local optima and enhance the search stability. Furthermore, IVYPSO adaptively selects between local growth and global diffusion strategies based on the fitness difference between the current solution and the global best, thereby improving the solution diversity and convergence accuracy. To assess the effectiveness of IVYPSO, comprehensive experiments were conducted on 26 standard benchmark functions and three real-world engineering optimization problems, with the performance compared against 11 state-of-the-art intelligent optimization algorithms. The results demonstrate that IVYPSO outperformed most competing algorithms on the majority of benchmark functions, exhibiting superior search capability and robustness. In the stability analysis, IVYPSO consistently achieved the global optimum across multiple runs on the three engineering cases with reduced computational time, attaining a 100% success rate (SR), which highlights its strong global optimization ability and excellent repeatability. Full article

28 pages, 81257 KiB

Open AccessArticle

The Drosophila Connectome as a Computational Reservoir for Time-Series Prediction

by Leone Costi, Alexander Hadjiivanov, Dominik Dold, Zachary F. Hale and Dario Izzo

Biomimetics 2025, 10(5), 341; https://doi.org/10.3390/biomimetics10050341 - 21 May 2025

Abstract

In this work, we explore the possibility of using the topology and weight distribution of the connectome of a Drosophila, or fruit fly, as a reservoir for multivariate chaotic time-series prediction. Based on the information taken from the recently released full connectome, [...] Read more.

In this work, we explore the possibility of using the topology and weight distribution of the connectome of a Drosophila, or fruit fly, as a reservoir for multivariate chaotic time-series prediction. Based on the information taken from the recently released full connectome, we create the connectivity matrix of an Echo State Network. Then, we use only the most connected neurons and implement two possible selection criteria, either preserving or breaking the relative proportion of different neuron classes which are also included in the documented connectome, to obtain a computationally convenient reservoir. We then investigate the performance of such architectures and compare them to state-of-the-art reservoirs. The results show that the connectome-based architecture is significantly more resilient to overfitting compared to the standard implementation, particularly in cases already prone to overfitting. To further isolate the role of topology and synaptic weights, hybrid reservoirs with the connectome topology but random synaptic weights and the connectome weights but random topologies are included in the study, demonstrating that both factors play a role in the increased overfitting resilience. Finally, we perform an experiment where the entire connectome is used as a reservoir. Despite the much higher number of trained parameters, the reservoir remains resilient to overfitting and has a lower normalized error, under 2%, at lower regularisation, compared to all other reservoirs trained with higher regularisation. Full article

(This article belongs to the Special Issue Advances in Biomimetics: Patents from Nature)

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24 pages, 2300 KiB

Open AccessReview

Adverse Effects Due to the Use of Upper Limbs Exoskeletons in the Work Environment: A Scoping Review

by Omar Flor-Unda, Rafael Arcos-Reina, Susana Nunez-Nagy and Bernardo Alarcos

Biomimetics 2025, 10(5), 340; https://doi.org/10.3390/biomimetics10050340 - 21 May 2025

Abstract

Both for design issues and for the study, analysis, and understanding of the interaction of workers with exoskeletons, the study of adverse effects provides criteria to improve the design of more efficient exoskeletons with better ergonomics and long-term usability. In this work, a [...] Read more.

Both for design issues and for the study, analysis, and understanding of the interaction of workers with exoskeletons, the study of adverse effects provides criteria to improve the design of more efficient exoskeletons with better ergonomics and long-term usability. In this work, a scoping review was carried out on adverse effects due to the prolonged use of upper-limb exoskeletons, which have been evidenced in the scientific literature. The causes of the effects are described in terms of their impacts on the physiological, psychological, and technological aspects that affect the user. A scoping review of articles of the last ten years on negative effects of upper-extremity exoskeletons for industrial tasks was carried out following the guidelines of the PRISMA^® methodology with three phases: formulation of questions, definition of scopes and exhaustive search in SCOPUS, Web of Science, Science Direct, Taylor & Francis, and PubMed. The selection was made by two review authors with a Cohen’s Kappa coefficient of 0.9530, indicating high agreement. The effectiveness of upper-limb exoskeletons depends on the environment and the task, so an adaptable ergonomic design, field validations, and standards are required to ensure their functionality and acceptance. Use of exoskeletons mainly activates the posterior deltoid and latissimus dorsi and reduces the activity of muscles such as the trapezius, pectoralis major, anterior and middle deltoids, biceps brachii, brachioradialis, and flexor carpi radialis. Full article

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39 pages, 2065 KiB

Open AccessReview

Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis

by Andres Emilio Hurtado-Perez, Manuel Toledano-Ayala, Irving A. Cruz-Albarran, Alejandra Lopez-Zúñiga, Jesús Adrián Moreno-Perez, Alejandra Álvarez-López, Juvenal Rodriguez-Resendiz and Carlos A. Perez-Ramirez

Biomimetics 2025, 10(5), 339; https://doi.org/10.3390/biomimetics10050339 - 20 May 2025

Abstract

This review provides an in-depth examination of the technologies and methods used for the acquisition and processing of kinetic and kinematic variables in human motion analysis. This review analyzes the capabilities and limitations of motion-capture cameras (MCCs), inertial measurement units (IMUs), force platforms, [...] Read more.

This review provides an in-depth examination of the technologies and methods used for the acquisition and processing of kinetic and kinematic variables in human motion analysis. This review analyzes the capabilities and limitations of motion-capture cameras (MCCs), inertial measurement units (IMUs), force platforms, and other prototype technologies. The role of advanced processing techniques, including filtering and transformation methods, and the increasing integration of artificial intelligence (AI) and machine learning (ML) for data classification is also discussed. These advancements enhance the precision and efficiency of biomechanical analyses, paving the way for more accurate assessments of human movement patterns. The review concludes by providing guidelines for the effective application of these technologies in both clinical and research settings, emphasizing the need for comprehensive validation to ensure reliability. This comprehensive overview serves as a valuable resource for researchers and professionals in the field of biomechanics, guiding the selection and application of appropriate technologies and methodologies for human movement analysis. Full article

(This article belongs to the Special Issue Biomimetic Approaches in Healthcare—Innovations Inspired by Nature: 2nd Edition)

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24 pages, 6944 KiB

Open AccessArticle

An Enhanced Starfish Optimization Algorithm via Joint Strategy and Its Application in Ultra-Wideband Indoor Positioning

by Yu Liu, Maosheng Fu, Zhengyu Liu, Huaiqing Liu, Wei Peng, Ling Li, Yang Yang, Xiancun Zhou and Chaochuan Jia

Biomimetics 2025, 10(5), 338; https://doi.org/10.3390/biomimetics10050338 - 20 May 2025

Abstract

The starfish optimization algorithm (SFOA) is a metaheuristic evolutionary intelligence algorithm with a great global search capability and strong adaptability. Although the SFOA has a good global search capability, it is not accurate enough in local search and converges slowly. To further enhance [...] Read more.

The starfish optimization algorithm (SFOA) is a metaheuristic evolutionary intelligence algorithm with a great global search capability and strong adaptability. Although the SFOA has a good global search capability, it is not accurate enough in local search and converges slowly. To further enhance this convergence ability and global optimization ability, an enhanced starfish optimization algorithm (SFOAL) is proposed that combines sine chaotic mapping, t-distribution mutation, and logarithmic spiral reverse learning. The SFOAL can remarkably enhance both the global and local convergence capabilities of the algorithm, leading to a more rapid convergence speed and greater stability. In total, 23 benchmark functions and CEC2021 were used to test the development, search, and convergence capabilities of the SFOAL. The SFOAL was compared in detail with other algorithms. The experimental results demonstrated that the overall performance of the SFOAL was better than that of other algorithms, and the joint strategy could effectively balance the development and search capabilities to obtain stronger global and local optimization capabilities. For solving practical problems, the SFOAL was used to optimize the back propagation (BP) neural network to solve the ultra-wideband line-of-sight positioning problem. The results showed that the SFOAL-BP neural network had a smaller average position error compared to the random BP neural network and the SFOA-BP neural network, so it can be used to solve practical application problems. Full article

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32 pages, 3652 KiB

Open AccessReview

A Review of Wearable Back-Support Exoskeletons for Preventing Work-Related Musculoskeletal Disorders

by Yanping Qu, Xupeng Wang, Xinyao Tang, Xiaoyi Liu, Yuyang Hao, Xinyi Zhang, Hongyan Liu and Xinran Cheng

Biomimetics 2025, 10(5), 337; https://doi.org/10.3390/biomimetics10050337 - 20 May 2025

Abstract

Long-term manual material handling (MMH) work leads to the trend of the younger onset of work-related musculoskeletal disorders (WMSDs), with low back pain (LBP) being the most common, which causes great trouble for both society and patients. To effectively prevent LBP and provide [...] Read more.

Long-term manual material handling (MMH) work leads to the trend of the younger onset of work-related musculoskeletal disorders (WMSDs), with low back pain (LBP) being the most common, which causes great trouble for both society and patients. To effectively prevent LBP and provide support for workers engaged in MMH work, wearable lumbar assistive exoskeletons have played a key role in industrial scenarios. This paper divides wearable lumbar assistive exoskeletons into powered, unpowered, and quasi-passive types, systematically reviews the research status of each type of exoskeleton, and compares and discusses the key factors such as driving mode, mechanical structure, control strategy, performance evaluation, and human–machine interaction. It is found that many studies focus on the assistive performance, human–machine coupling coordination, and adaptability of wearable lumbar assistive exoskeletons. At the same time, the analysis results show that there are many types of performance evaluation indicators, but a unified and standardized evaluation method and system are still lacking. This paper analyzes current research findings, identifies existing issues, and provides recommendations for future research. This study provides a theoretical basis and design ideas for the development of wearable lumbar assistive exoskeleton systems. Full article

(This article belongs to the Special Issue Bionic Wearable Robotics and Intelligent Assistive Technologies)

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27 pages, 1670 KiB

Open AccessArticle

Bio-Inspired Observability Enhancement Method for UAV Target Localization and Sensor Bias Estimation with Bearing-Only Measurement

by Qianshuai Wang, Zeyuan Li, Jicheng Peng and Kelin Lu

Biomimetics 2025, 10(5), 336; https://doi.org/10.3390/biomimetics10050336 - 20 May 2025

Abstract

This paper addresses the problem of observability analysis and enhancement for UAV target localization and sensor bias estimation with bearing-only measurement. Inspired by the compound eye vision, a bio-inspired observability analysis method is proposed for stochastic systems. Furthermore, a performance metric that can [...] Read more.

This paper addresses the problem of observability analysis and enhancement for UAV target localization and sensor bias estimation with bearing-only measurement. Inspired by the compound eye vision, a bio-inspired observability analysis method is proposed for stochastic systems. Furthermore, a performance metric that can be utilized in UAV trajectory optimization for observability enhancement of the target localization system is formulated based on maximum mean discrepancy. The performance metric and the distance of the UAV relative to the target are utilized as objective functions for trajectory optimization. To determine the decision variables (the UAV’s velocity and turn rate) for UAV maneuver decision making, a multi-objective optimization framework is constructed, and is subsequently solved via the nonlinear constrained multi-objective whale optimization algorithm. Finally, the analytical results are validated through numerical simulations and comparative analyses. The proposed method demonstrates superior convergence in both target localization and sensor bias estimation. The nonlinear constrained multi-objective whale optimization algorithm achieves minimal values for both generational distance and inverted generational distance, demonstrating superior convergence and diversity characteristics. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 3rd Edition)

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31 pages, 15164 KiB

Open AccessArticle

Coordinated Locomotion Control for a Quadruped Robot with Bionic Parallel Torso

by Yaguang Zhu, Ao Cao, Zhimin He, Mengnan Zhou and Ruyue Li

Biomimetics 2025, 10(5), 335; https://doi.org/10.3390/biomimetics10050335 - 20 May 2025

Abstract

This paper presents the design and control of a quadruped robot equipped with a six-degree-of-freedom (6-DOF) bionic active torso based on a parallel mechanism. Inspired by the compliant and flexible torsos of quadrupedal mammals, the proposed torso structure enhances locomotion performance [...] Read more.

This paper presents the design and control of a quadruped robot equipped with a six-degree-of-freedom (6-DOF) bionic active torso based on a parallel mechanism. Inspired by the compliant and flexible torsos of quadrupedal mammals, the proposed torso structure enhances locomotion performance by enabling coordinated motion between the torso and legs. A complete kinematic model of the bionic torso and the whole body of the quadruped robot is developed. To address the variation in inertial properties caused by torso motion, a model predictive control (MPC) strategy with a variable center of mass (CoM) is proposed for integrated whole-body motion control. Comparative simulations under trot gait are conducted between rigid-torso and active-torso configurations. Results show that the active torso significantly improves gait flexibility, postural stability, and locomotion efficiency. This study provides a new approach to enhancing biomimetic locomotion in quadruped robots through active torso-leg coordination. Full article

(This article belongs to the Special Issue Recent Advances in Bioinspired Robot and Intelligent Systems)

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12 pages, 4832 KiB

Open AccessArticle

Preparation and Performance of Biomimetic Zebra-Striped Wood-Based Photothermal Evaporative Materials

by Zebin Zhao, Wenxuan Wang, Zhichen Ba, Yuze Zhang, Hongbo Xu and Daxin Liang

Biomimetics 2025, 10(5), 334; https://doi.org/10.3390/biomimetics10050334 - 20 May 2025

Abstract

An efficient solar water evaporator is an important strategy for addressing the problem of water shortage. Constructing high-performance solar interfacial evaporators through bionic design has become a crucial approach for performance enhancement. Through the study of zebra patterns, it has been found that [...] Read more.

An efficient solar water evaporator is an important strategy for addressing the problem of water shortage. Constructing high-performance solar interfacial evaporators through bionic design has become a crucial approach for performance enhancement. Through the study of zebra patterns, it has been found that the black-and-white alternating patterns generate vortices on the surface of the zebra’s skin, thereby reducing the temperature. By utilizing the vortices brought about by the temperature difference, the design of a solar water evaporator is created based on the bionic zebra pattern, so as to improve its water evaporation performance. In this work, green and sustainable wood is used as the base of the evaporator, and the bionic design of zebra stripes is adopted. Meanwhile, the following research is conducted: The wood is cut into thin slices with dimensions of 30 × 30 × 5 mm³, and a delignification treatment is performed. Tannic acid-Fe ions are used as the photothermal material for functionalization. A series of stable patterned water evaporators based on delignification wood loaded with tannic acid-Fe ion complex (TA-Fe³⁺) are successfully prepared. Among them, the wood-based solar water evaporator with 3 mm zebra stripes exhibits excellent photothermal water evaporation performance, achieving a water evaporation rate of 1.44 kg·m⁻²·h⁻¹ under the illumination intensity of one sun. Its water evaporation performance is significantly superior to that of other coating patterns, proving that the bionic design of zebra patterns is effective and can improve water evaporation efficiency. This work provides new insights into the development of safe and environmentally friendly solar interfacial water evaporation materials through bionic design. Full article

(This article belongs to the Section Biomimetics of Materials and Structures)

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30 pages, 1927 KiB

Open AccessArticle

Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms

by Zengkai Wang, Weizhi Liao, Xiaoyun Xia, Zijia Wang and Yaolong Duan

Biomimetics 2025, 10(5), 333; https://doi.org/10.3390/biomimetics10050333 - 20 May 2025

Abstract

Routing and scheduling in Time-Sensitive Networking (TSN) is an NP-hard problem. In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm. Specifically, we introduce a flow grouping method that leverages the greatest common divisor to optimize [...] Read more.

Routing and scheduling in Time-Sensitive Networking (TSN) is an NP-hard problem. In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm. Specifically, we introduce a flow grouping method that leverages the greatest common divisor to optimize flow aggregation. On this basis, we develop a flow routing strategy that employs a genetic algorithm, where the evaluation function considers not only flow combinability but also path length and network load. By exploiting the non-combinable properties of flows, we effectively reduce the search space for the genetic algorithm. Furthermore, we design a scheduling method based on differential evolution algorithms tailored to TSN’s requirements of zero jitter and no frame loss. We propose a gene coding method and rigorously prove its correctness, which significantly reduces the search space of the differential evolution algorithm. The experimental results demonstrate that our approach enables more flows to traverse along the shortest path compared to both k-shortest path methods and integer linear programming approaches, while achieving a faster execution time in large-scale scheduling scenarios. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 3rd Edition)

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16 pages, 1693 KiB

Open AccessArticle

A Gaussian Mixture Model-Based Unsupervised Dendritic Artificial Visual System for Motion Direction Detection

by Zhiyu Qiu, Yuxiao Hua, Tianqi Chen, Yuki Todo, Zheng Tang, Delai Qiu and Chunping Chu

Biomimetics 2025, 10(5), 332; https://doi.org/10.3390/biomimetics10050332 - 19 May 2025

Abstract

Motion perception is a fundamental function of biological visual systems, enabling organisms to navigate dynamic environments, detect threats, and track moving objects. Inspired by the mechanisms of biological motion processing, we propose an Unsupervised Artificial Visual System for motion direction detection. Unlike traditional [...] Read more.

Motion perception is a fundamental function of biological visual systems, enabling organisms to navigate dynamic environments, detect threats, and track moving objects. Inspired by the mechanisms of biological motion processing, we propose an Unsupervised Artificial Visual System for motion direction detection. Unlike traditional supervised learning approaches, our model employs unsupervised learning to classify local motion direction detection neurons and group those with similar directional preferences to form macroscopic motion direction detection neurons. The activation of these neurons is proportional to the received input, and the neuron with the highest activation determines the macroscopic motion direction of the object. The proposed system consists of two layers: a local motion direction detection layer and an unsupervised global motion direction detection layer. For local motion detection, we adopt the Local Motion Detection Neuron (LMDN) model proposed in our previous work, which detects motion in eight different directions. The outputs of these neurons serve as inputs to the global motion direction detection layer, which employs a Gaussian Mixture Model (GMM) for unsupervised clustering. GMM, a probabilistic clustering method, effectively classifies local motion detection neurons according to their preferred directions, aligning with biological principles of sensory adaptation and probabilistic neural processing. Through repeated exposure to motion stimuli, our model self-organizes to detect macroscopic motion direction without the need for labeled data. Experimental results demonstrate that the GMM-based global motion detection layer successfully classifies motion direction signals, forming structured motion representations akin to biological visual systems. Furthermore, the system achieves motion direction detection accuracy comparable to previous supervised models while offering a more biologically plausible mechanism. This work highlights the potential of unsupervised learning in artificial vision and contributes to the development of adaptive motion perception models inspired by neural computation. Full article

(This article belongs to the Special Issue Biomimetics and Bioinspired Artificial Intelligence Applications: 2nd Edition)

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24 pages, 6344 KiB

Open AccessArticle

Multi-Threshold Remote Sensing Image Segmentation Based on Improved Black-Winged Kite Algorithm

by Yi Zhang, Xinyu Liu, Wei Sun, Tianshu You and Xin Qi

Biomimetics 2025, 10(5), 331; https://doi.org/10.3390/biomimetics10050331 - 19 May 2025

Abstract

This paper proposes an adaptive multi-threshold image segmentation method named IBKA-OTSU to address the limitations of existing deep learning-based image segmentation methods, particularly their heavy reliance on large-scale annotated datasets and high computational complexity. The proposed algorithm significantly enhances the capability of complex [...] Read more.

This paper proposes an adaptive multi-threshold image segmentation method named IBKA-OTSU to address the limitations of existing deep learning-based image segmentation methods, particularly their heavy reliance on large-scale annotated datasets and high computational complexity. The proposed algorithm significantly enhances the capability of complex remote sensing scenarios by systematic improvements to core algorithm components, including population initialization strategy, attack behavior patterns, migration mechanisms, and opposition-based learning strategy. The improved intelligent optimization algorithm is innovatively integrated with the OTSU threshold method to establish a multi-threshold segmentation model specifically designed for remote sensing imagery. Experimental validation using representative samples from the ISPRS Potsdam benchmark dataset demonstrates that our IBKA-optimized OTSU multi-threshold segmentation method outperforms traditional IBKA-optimized pulse coupled neural network (PCNN) approaches in remote sensing image analysis. Quantitative evaluations reveal substantial improvements in the dice coefficient across six randomly selected remote sensing images, achieving performance enhancements of 7.76%, 11.99%, 30.75%, 22.91%, 44.37%, and 18.55%, respectively. This research provides an effective technical solution for intelligently interpreting remote sensing imagery in resource-constrained environments, demonstrating significant theoretical value and practical application potential in engineering implementations. Full article

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21 pages, 3697 KiB

Open AccessArticle

Research and Design of a Medial-Support Exoskeleton Chair

by Wenzhou Lin, Yin Xiong, Chunqiang Zhang, Xupeng Wang and Bing Han

Biomimetics 2025, 10(5), 330; https://doi.org/10.3390/biomimetics10050330 - 18 May 2025

Abstract

To address lower limb fatigue in workers engaged in prolonged standing, this study proposes a structural design for a medial-support passive exoskeleton seat. The design incorporates support rods positioned along the medial aspect of the user’s lower limbs and features an adaptive telescopic [...] Read more.

To address lower limb fatigue in workers engaged in prolonged standing, this study proposes a structural design for a medial-support passive exoskeleton seat. The design incorporates support rods positioned along the medial aspect of the user’s lower limbs and features an adaptive telescopic rod system, enhancing sitting stability and reducing collision risks in workplace environments. Human motion capture technology was used to collect kinematic data of the lower limbs, and a mathematical model of center-of-gravity variation was developed to calculate and optimize the exoskeleton’s structural parameters. Static analysis was performed using ANSYS software (2025 R1) to evaluate the structural integrity of the design. The effectiveness of the exoskeleton seat was validated through surface electromyography (sEMG) experiments, with results showing that the exoskeleton significantly reduces lower limb muscle load by 49.2% to 72.9%. Additionally, force plate experiments demonstrated that the exoskeleton seat improves stability, with a 39.2% reduction in the average displacement of the center of pressure (CoP), confirming its superior postural alignment and balance. The design was also compared with existing exoskeleton chairs, showing comparable or better performance in terms of muscle load reduction, stability, and overall effectiveness. Full article

(This article belongs to the Special Issue Bionic Wearable Robotics and Intelligent Assistive Technologies)

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22 pages, 8094 KiB

Open AccessArticle

Corrugation at the Trailing Edge Enhances the Aerodynamic Performance of a Three-Dimensional Wing During Gliding Flight

by Kaipeng Li, Na Xu, Licheng Zhong and Xiaolei Mou

Biomimetics 2025, 10(5), 329; https://doi.org/10.3390/biomimetics10050329 - 17 May 2025

Abstract

Dragonflies exhibit remarkable flight capabilities, and their wings feature corrugated structures that are distinct from conventional airfoils. This study investigates the aerodynamic effects of three corrugation parameters on gliding performance at a Reynolds number of 1350 and angles of attack ranging from 0° [...] Read more.

Dragonflies exhibit remarkable flight capabilities, and their wings feature corrugated structures that are distinct from conventional airfoils. This study investigates the aerodynamic effects of three corrugation parameters on gliding performance at a Reynolds number of 1350 and angles of attack ranging from 0° to 20°: (1) chordwise corrugation position, (2) linear variation in corrugation amplitude toward the trailing edge, and (3) the number of trailing-edge corrugations. The results show that when corrugation structures are positioned closer to the trailing edge, they generate localized vortices in the mid-forward region of the upper surface, thereby enhancing aerodynamic performance. Further studies show that a linear increase in corrugation amplitude toward the trailing edge significantly delays the shedding of the leading-edge vortex (LEV), produces a more coherent LEV, and reduces the number of vortices within the corrugation grooves on the lower surface. Consequently, the lift coefficient is maximized with an enhancement of 28.99%. Additionally, reducing the number of trailing-edge corrugations makes the localized vortices on the upper surface approach the trailing edge and merge into larger, more continuous LEVs. The vortices on the lower surface grooves also decrease in number, and the lift coefficient is maximally increased by 20.09%. Full article

(This article belongs to the Special Issue Bio-Inspired Propulsion and Fluid Mechanics)

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19 pages, 26314 KiB

Open AccessArticle

Effects of Wing Kinematics on Aerodynamics Performance for a Pigeon-Inspired Flapping Wing

by Tao Wu, Kai Wang, Qiang Jia and Jie Ding

Biomimetics 2025, 10(5), 328; https://doi.org/10.3390/biomimetics10050328 - 17 May 2025

Abstract

The wing kinematics of birds plays a significant role in their excellent unsteady aerodynamic performance. However, most studies investigate the influence of different kinematic parameters of flapping wings on their aerodynamic performance based on simple harmonic motions, which neglect the aerodynamic effects of [...] Read more.

The wing kinematics of birds plays a significant role in their excellent unsteady aerodynamic performance. However, most studies investigate the influence of different kinematic parameters of flapping wings on their aerodynamic performance based on simple harmonic motions, which neglect the aerodynamic effects of the real flapping motion. The purpose of this article was to study the effects of wing kinematics on aerodynamic performance for a pigeon-inspired flapping wing. In this article, the dynamic geometric shape of a flapping wing was reconstructed based on data of the pigeon wing profile. The 3D wingbeat kinematics of a flying pigeon was extracted from the motion trajectories of the wingtip and the wrist during cruise flight. Then, we used a hybrid RANS/LES method to study the effects of wing kinematics on the aerodynamic performance and flow patterns of the pigeon-inspired flapping wing. First, we investigated the effects of dynamic spanwise twisting on the lift and thrust performance of the flapping wing. Numerical results show that the twisting motion weakens the leading-edge vortex (LEV) on the upper surface of the wing during the downstroke by reducing the effective angle of attack, thereby significantly reducing the time-averaged lift and power consumption. Then, we further studied the effects of the 3D sweeping motion on the aerodynamic performance of the flapping wing. Backward sweeping reduces the wing area and weakens the LEV on the lower surface of the wing, which increases the lift and reduces the aerodynamic power consumption significantly during the upstroke, leading to a high lift efficiency. These conclusions are significant for improving the aerodynamic performance of bionic flapping-wing micro air vehicles. Full article

(This article belongs to the Special Issue Bio-Inspired Flapping Wing Aerodynamics for Propulsion and Power Generation: 2nd Edition)

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20 pages, 5890 KiB

Open AccessArticle

A Mantis-Inspired Multi-Quadrupole Adaptive Landing Gear Design and Performance Study

by Yichen Chu, Zhifeng Lv, Shuo Gu, Yida Wang and Tianbiao Yu

Biomimetics 2025, 10(5), 327; https://doi.org/10.3390/biomimetics10050327 - 17 May 2025

Abstract

This paper investigates and designs an adaptive landing gear inspired by the passive adaptation mechanism of the praying mantis on intricate landing surfaces to improve the landing safety of unmanned aerial vehicles (UAVs) in complicated terrain situations. A new passive adaptation structure utilizing [...] Read more.

This paper investigates and designs an adaptive landing gear inspired by the passive adaptation mechanism of the praying mantis on intricate landing surfaces to improve the landing safety of unmanned aerial vehicles (UAVs) in complicated terrain situations. A new passive adaptation structure utilizing multiple mutually perpendicular four-bar mechanisms is developed to address the limitations of the typical fixed truss structure landing gear. The system employs a singular laser range sensor locking mechanism, thereby significantly diminishing the control and structural complexity. The design incorporates a parallelogram mechanism to achieve the adaptation of different height differences through the mechanism’s deformation. The buffer damping mechanism and locking mechanism are engineered to augment the safety of the landing process and enhance the energy recovery rate. The circuit design employs the STC32G and Keil C251 microcontroller for development, thus achieving the automatic control of the landing gear. The experimental results demonstrate that the adaptive landing gear suggested in this paper can successfully adjust to the complex landing surface and has a good energy recovery performance. This aids in the advancement of UAVs in the field of complex environment applications and offers a safe, dependable, and creative solution for UAV landing scenarios in complex terrains. Full article

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