Biomimetics最新文献

{"title":"A Particle Swarm Optimization-Guided Ivy Algorithm for Global Optimization Problems.","authors":"Kaifan Zhang, Fujiang Yuan, Yang Jiang, Zebing Mao, Zihao Zuo, Yanhong Peng","doi":"10.3390/biomimetics10050342","DOIUrl":"10.3390/biomimetics10050342","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The <i>Drosophila</i> Connectome as a Computational Reservoir for Time-Series Prediction.","authors":"Leone Costi, Alexander Hadjiivanov, Dominik Dold, Zachary F Hale, Dario Izzo","doi":"10.3390/biomimetics10050341","DOIUrl":"10.3390/biomimetics10050341","url":null,"abstract":"<p><p>In this work, we explore the possibility of using the topology and weight distribution of the connectome of a <i>Drosophila</i>, 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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Enhanced Starfish Optimization Algorithm via Joint Strategy and Its Application in Ultra-Wideband Indoor Positioning.","authors":"Yu Liu, Maosheng Fu, Zhengyu Liu, Huaiqing Liu, Wei Peng, Ling Li, Yang Yang, Xiancun Zhou, Chaochuan Jia","doi":"10.3390/biomimetics10050338","DOIUrl":"10.3390/biomimetics10050338","url":null,"abstract":"<p><p>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, <i>t</i>-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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109220/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coordinated Locomotion Control for a Quadruped Robot with Bionic Parallel Torso.","authors":"Yaguang Zhu, Ao Cao, Zhimin He, Mengnan Zhou, Ruyue Li","doi":"10.3390/biomimetics10050335","DOIUrl":"10.3390/biomimetics10050335","url":null,"abstract":"<p><p>This paper presents the design and control of a quadruped robot equipped with a six-degree-of-freedom (6-<i>DOF</i>) 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 (<i>MPC</i>) strategy with a variable center of mass (<i>CoM</i>) 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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12108630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144148915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review of Wearable Back-Support Exoskeletons for Preventing Work-Related Musculoskeletal Disorders.","authors":"Yanping Qu, Xupeng Wang, Xinyao Tang, Xiaoyi Liu, Yuyang Hao, Xinyi Zhang, Hongyan Liu, Xinran Cheng","doi":"10.3390/biomimetics10050337","DOIUrl":"10.3390/biomimetics10050337","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12108747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preparation and Performance of Biomimetic Zebra-Striped Wood-Based Photothermal Evaporative Materials.","authors":"Zebin Zhao, Wenxuan Wang, Zhichen Ba, Yuze Zhang, Hongbo Xu, Daxin Liang","doi":"10.3390/biomimetics10050334","DOIUrl":"10.3390/biomimetics10050334","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12108723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis.","authors":"Andres Emilio Hurtado-Perez, Manuel Toledano-Ayala, Irving A Cruz-Albarran, Alejandra Lopez-Zúñiga, Jesús Adrián Moreno-Perez, Alejandra Álvarez-López, Juvenal Rodriguez-Resendiz, Carlos A Perez-Ramirez","doi":"10.3390/biomimetics10050339","DOIUrl":"10.3390/biomimetics10050339","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109401/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms.","authors":"Zengkai Wang, Weizhi Liao, Xiaoyun Xia, Zijia Wang, Yaolong Duan","doi":"10.3390/biomimetics10050333","DOIUrl":"10.3390/biomimetics10050333","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-Inspired Observability Enhancement Method for UAV Target Localization and Sensor Bias Estimation with Bearing-Only Measurement.","authors":"Qianshuai Wang, Zeyuan Li, Jicheng Peng, Kelin Lu","doi":"10.3390/biomimetics10050336","DOIUrl":"10.3390/biomimetics10050336","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109225/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Gaussian Mixture Model-Based Unsupervised Dendritic Artificial Visual System for Motion Direction Detection.","authors":"Zhiyu Qiu, Yuxiao Hua, Tianqi Chen, Yuki Todo, Zheng Tang, Delai Qiu, Chunping Chu","doi":"10.3390/biomimetics10050332","DOIUrl":"10.3390/biomimetics10050332","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12108726/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}