Biomimetics

28 pages, 1547 KiB

Open AccessReview

Brain–Computer Interfaces in Parkinson’s Disease Rehabilitation

by Emmanuel Ortega-Robles, Ruben I. Carino-Escobar, Jessica Cantillo-Negrete and Oscar Arias-Carrión

Biomimetics 2025, 10(8), 488; https://doi.org/10.3390/biomimetics10080488 - 23 Jul 2025

Parkinson’s disease (PD) is a progressive neurological disorder with motor and non-motor symptoms that are inadequately addressed by current pharmacological and surgical therapies. Brain–computer interfaces (BCIs), particularly those based on electroencephalography (eBCIs), provide a promising, non-invasive approach to personalized neurorehabilitation. This narrative review [...] Read more.

Parkinson’s disease (PD) is a progressive neurological disorder with motor and non-motor symptoms that are inadequately addressed by current pharmacological and surgical therapies. Brain–computer interfaces (BCIs), particularly those based on electroencephalography (eBCIs), provide a promising, non-invasive approach to personalized neurorehabilitation. This narrative review explores the clinical potential of BCIs in PD, discussing signal acquisition, processing, and control paradigms. eBCIs are well-suited for PD due to their portability, safety, and real-time feedback capabilities. Emerging neurophysiological biomarkers—such as beta-band synchrony, phase–amplitude coupling, and altered alpha-band activity—may support adaptive therapies, including adaptive deep brain stimulation (aDBS), as well as motor and cognitive interventions. BCIs may also aid in diagnosis and personalized treatment by detecting these cortical and subcortical patterns associated with motor and cognitive dysfunction in PD. A structured search identified 11 studies involving 64 patients with PD who used BCIs for aDBS, neurofeedback, and cognitive rehabilitation, showing improvements in motor function, cognition, and engagement. Clinical translation requires attention to electrode design and user-centered interfaces. Ethical issues, including data privacy and equitable access, remain critical challenges. As wearable technologies and artificial intelligence evolve, BCIs could shift PD care from intermittent interventions to continuous, brain-responsive therapy, potentially improving patients’ quality of life and autonomy. This review highlights BCIs as a transformative tool in PD management, although more robust clinical evidence is needed. Full article

(This article belongs to the Special Issue Advances in Brain–Computer Interfaces (BCI): Challenges and Opportunities)

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Graphical abstract

18 pages, 8296 KiB

Open AccessArticle

Survival Is Skin Deep: Toughness of the Outer Cactus Stem with Insights for Technical Envelopes

by Patricia Soffiatti, Natália O. Bonfante, Maria Clara L. Jaculiski and Nick P. Rowe

Biomimetics 2025, 10(8), 487; https://doi.org/10.3390/biomimetics10080487 - 23 Jul 2025

Abstract

Cacti are of interest for new bio-inspired technologies because of their remarkable adaptations to extreme environments. Recently, they have inspired functional designs from nano fibres to optimised buildings and architectures. We investigate the diversity of cactus skin properties in terms of toughness and [...] Read more.

Cacti are of interest for new bio-inspired technologies because of their remarkable adaptations to extreme environments. Recently, they have inspired functional designs from nano fibres to optimised buildings and architectures. We investigate the diversity of cactus skin properties in terms of toughness and resistance to cutting damage. Cacti are well known for their extreme adaptations to harsh environments, with soft, fleshy stems that expand and contract with water uptake and storage. This functioning is made possible by an extendable outer envelope (skin) and a fluted 3-dimensional structure of the stem. We explore the mechanical toughness and underlying structural organisation of the cactus skin in four species of cactus showing different growth forms. The toughness properties of the cactus skin is only one part of a multi-functional structure for surviving in extreme environments. The study suggests that survival involves a relatively “light” investment of tough materials in the outer envelope instead of a rigid “defensive” layer. This is capable of elastic deformation and enables water storage in challenging, arid environments. The main purpose of this article is to demonstrate the diversity of skin toughness and underlying structures in the biological world as providing potential new designs for technical envelopes. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Biomimetics of Materials, Functions, Structures and Processes 2025)

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15 pages, 2557 KiB

Open AccessArticle

Multiline Laser Interferometry for Non-Contact Dynamic Morphing of Hierarchical Surfaces

by Biagio Audia, Caterina Maria Tone, Pasquale Pagliusi, Alfredo Mazzulla, George Papavieros, Vassilios Constantoudis and Gabriella Cipparrone

Biomimetics 2025, 10(8), 486; https://doi.org/10.3390/biomimetics10080486 - 23 Jul 2025

Abstract

Hierarchical surface structuring is a critical aspect of advanced materials design, impacting fields ranging from optics to biomimetics. Among several laser-based methods for complex structuring of photo-responsive surfaces, the broadband vectorial interferometry proposed here offers unique performances. Such a method leverages a polychromatic [...] Read more.

Hierarchical surface structuring is a critical aspect of advanced materials design, impacting fields ranging from optics to biomimetics. Among several laser-based methods for complex structuring of photo-responsive surfaces, the broadband vectorial interferometry proposed here offers unique performances. Such a method leverages a polychromatic laser source, an unconventional choice for holographic encoding, to achieve deterministic multiscale surface structuring through interference light patterning. Azopolymer films are used as photosensitive substrates. By exploring the interaction between optomechanical stress modulations at different spatial periodicities induced within the polymer bulk, we demonstrate the emergence of hierarchical Fourier surfaces composed of multiple deterministic levels. These structures range from sub-micrometer to tens of micrometers scale, exhibiting a high degree of control over their morphology. The experimental findings reveal that the optical encoding scheme significantly influences the resulting topographies. The polarization light patterns lead to more regular and symmetric hierarchical structures compared to those obtained with intensity patterns, underscoring the role of vectorial light properties in controlling surface morphologies. The proposed method is fully scalable, compatible with more complex recording schemes (including multi-beam interference), and it is applicable to a wide range of advanced technological fields. These include optics and photonics (diffractive elements, polarimetric devices), biomimetic surfaces, topographical design, information encoding, and anti-counterfeiting, offering a rapid, reliable, and versatile strategy for high-precision surface structuring at a submicrometric scale. Full article

(This article belongs to the Special Issue Laser Photonics and Micro/Nano Fabrication: Towards Innovations in Biomimetic Surface Engineering)

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18 pages, 1592 KiB

Open AccessArticle

A List-Based Parallel Bacterial Foraging Algorithm for the Multiple Sequence Alignment Problem

by Ernesto Rios-Willars, María Magdalena Delabra-Salinas and Alfredo Reyes-Acosta

Biomimetics 2025, 10(8), 485; https://doi.org/10.3390/biomimetics10080485 - 23 Jul 2025

Abstract

A parallel bacterial foraging algorithm was developed for the multiple sequence alignment problem. Four sets of homologous genetic and protein sequences related to Alzheimer’s disease among various species were collected from the NCBI database for convergence analysis and performance comparison. The main question [...] Read more.

A parallel bacterial foraging algorithm was developed for the multiple sequence alignment problem. Four sets of homologous genetic and protein sequences related to Alzheimer’s disease among various species were collected from the NCBI database for convergence analysis and performance comparison. The main question was the following: is the bacterial foraging algorithm suitable for the multiple sequence alignment problem? Three versions of the algorithm were contrasted by performing a t-test and Mann–Whitney test based on the results of a 30-run scheme, focusing on fitness, execution time, and the number of function evaluations as performance metrics. Additionally, we conducted a performance comparison of the developed algorithm with the well-known Genetic Algorithm. The results demonstrated the consistent efficiency of the bacterial foraging algorithm, while the version of the algorithm based on gap deletion presented an increased number of function evaluations and excessive execution time. Overall, the first version of the developed algorithm was found to outperform the second version, based on its efficiency. Finally, we found that the third bacterial foraging algorithm version outperformed the Genetic Algorithm in the third phase of the experiment. The sequence sets, the algorithm’s Python 3.12 code and pseudocode, the data collected from the executions, and a GIF animation of the convergence on various different sets are available for download. Full article

(This article belongs to the Special Issue Exploration of Bio-Inspired Computing)

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19 pages, 2472 KiB

Open AccessArticle

Immunomodulation Through Fibroblast-Derived Extracellular Vesicles (EVs) Within 3D Polycaprolactone–Collagen Matrix

by Afsara Tasnim, Diego Jacho, Agustin Rabino, Jose Benalcazar, Rafael Garcia-Mata, Yakov Lapitsky and Eda Yildirim-Ayan

Biomimetics 2025, 10(8), 484; https://doi.org/10.3390/biomimetics10080484 - 22 Jul 2025

Abstract

Extracellular vesicles (EVs) have emerged as promising acellular tools for modulating immune responses for tissue engineering applications. This study explores the potential of human fibroblast-derived EVs delivered within a three-dimensional (3D) injectable scaffold composed of polycaprolactone (PCL) nanofibers and collagen (PNCOL) to reprogram [...] Read more.

Extracellular vesicles (EVs) have emerged as promising acellular tools for modulating immune responses for tissue engineering applications. This study explores the potential of human fibroblast-derived EVs delivered within a three-dimensional (3D) injectable scaffold composed of polycaprolactone (PCL) nanofibers and collagen (PNCOL) to reprogram macrophage behavior and support scaffold integrity under inflammatory conditions. EVs were successfully isolated from human fibroblasts using ultracentrifugation and characterized for purity, size distribution and surface markers (CD63 and CD9). Macrophage-laden PNCOL scaffolds were prepared under three conditions: macrophage-only (MP), fibroblast co-encapsulated (F-MP), and EV-encapsulated (EV-MP) groups. Structural integrity was assessed via scanning electron microscopy and Masson’s trichrome staining, while immunomodulatory effects were evaluated through metabolic assays, gene expression profiling, and immunohistochemistry for macrophage polarization markers (CD80, CD206). When co-encapsulated with pro-inflammatory (M1) macrophages in PNCOL scaffolds, fibroblast-derived EVs preserved scaffold structure and significantly enhanced macrophage metabolic activity compared to the control (MP) and other experimental group (F-MP). The gene expression and immunohistochemistry data demonstrated substantial upregulation of anti-inflammatory markers (TGF-β, CD163, and CCL18) and surface protein CD206, indicating a phenotypic shift toward M2-like macrophages for EV-encapsulated scaffolds relative to the other groups. The findings of this study demonstrate that fibroblast-derived EVs integrated into injectable PCL–collagen scaffolds offer a viable, cell-free approach to modulate inflammation, preserve scaffold structure, and support regenerative healing. This strategy holds significant promise for advancing immuno-instructive platforms in regenerative medicine, particularly in settings where conventional cell therapies face limitations in survival, cost, or safety. Full article

(This article belongs to the Special Issue Biomimetic Application on Applied Bioengineering)

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54 pages, 2471 KiB

Open AccessSystematic Review

Technical Functions of Digital Wearable Products (DWPs) in the Consumer Acceptance Model: A Systematic Review and Bibliometric Analysis with A Biomimetic Perspective

by Liu Yuxin, Sarah Abdulkareem Salih and Nazlina Shaari

Biomimetics 2025, 10(8), 483; https://doi.org/10.3390/biomimetics10080483 - 22 Jul 2025

Abstract

Design and use of wearable technology have grown exponentially, particularly in consumer products and service sectors, e.g., healthcare. However, there is a lack of a comprehensive understanding of wearable technology in consumer acceptance. This systematic review utilized a PRISMA on peer-reviewed articles published [...] Read more.

Design and use of wearable technology have grown exponentially, particularly in consumer products and service sectors, e.g., healthcare. However, there is a lack of a comprehensive understanding of wearable technology in consumer acceptance. This systematic review utilized a PRISMA on peer-reviewed articles published between 2014 and 2024 and collected on WoS, Scopus, and ScienceDirect. A total of 38 full-text articles were systematically reviewed and analyzed using bibliometric, thematic, and descriptive analysis to understand the technical functions of digital wearable products (DWPs) in consumer acceptance. The findings revealed four key functions: (i) wearable technology, (ii) appearance and design, (iii) biomimetic innovation, and (iv) security and privacy, found in eight types of DWPs, among them smartwatches, medical robotics, fitness devices, and wearable fashions, significantly predicted the customers’ acceptance moderated by the behavioral factors. The review also identified five key outcomes: health and fitness, enjoyment, social value, biomimicry, and market growth. The review proposed a comprehensive acceptance model that combines biomimetic principles and AI-driven features into the technical functions of the technical function model (TAM) while addressing security and privacy concerns. This approach contributes to the extended definition of TAM in wearable technology, offering new pathways for biomimetic research in smart devices and robotics. Full article

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

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47 pages, 10439 KiB

Open AccessArticle

Adaptive Nonlinear Bernstein-Guided Parrot Optimizer for Mural Image Segmentation

by Jianfeng Wang, Jiawei Fan, Xiaoyan Zhang and Bao Qian

Biomimetics 2025, 10(8), 482; https://doi.org/10.3390/biomimetics10080482 - 22 Jul 2025

Abstract

During the long-term preservation of murals, the degradation of mural image information poses significant challenges to the restoration and conservation of world cultural heritage. Currently, mural conservation scholars focus on image segmentation techniques for mural restoration and protection. However, existing image segmentation methods [...] Read more.

During the long-term preservation of murals, the degradation of mural image information poses significant challenges to the restoration and conservation of world cultural heritage. Currently, mural conservation scholars focus on image segmentation techniques for mural restoration and protection. However, existing image segmentation methods suffer from suboptimal segmentation quality. To improve mural image segmentation, this study proposes an efficient mural image segmentation method termed Adaptive Nonlinear Bernstein-guided Parrot Optimizer (ANBPO) by integrating an adaptive learning strategy, a nonlinear factor, and a third-order Bernstein-guided strategy into the Parrot Optimizer (PO). In ANBPO, First, to address PO’s limited global exploration capability, the adaptive learning strategy is introduced. By considering individual information disparities and learning behaviors, this strategy effectively enhances the algorithm’s global exploration, enabling a thorough search of the solution space. Second, to mitigate the imbalance between PO’s global exploration and local exploitation phases, the nonlinear factor is proposed. Leveraging its adaptability and nonlinear curve characteristics, this factor improves the algorithm’s ability to escape local optimal segmentation thresholds. Finally, to overcome PO’s inadequate local exploitation capability, the third-order Bernstein-guided strategy is introduced. By incorporating the weighted properties of third-order Bernstein polynomials, this strategy comprehensively evaluates individuals with diverse characteristics, thereby enhancing the precision of mural image segmentation. ANBPO was applied to segment twelve mural images. The results demonstrate that, compared to competing algorithms, ANBPO achieves a 91.6% win rate in fitness function values while outperforming them by 67.6%, 69.4%, and 69.7% in PSNR, SSIM, and FSIM metrics, respectively. These results confirm that the ANBPO algorithm can effectively segment mural images while preserving the original feature information. Thus, it can be regarded as an efficient mural image segmentation algorithm. Full article

(This article belongs to the Special Issue Nature-Inspired Metaheuristic Optimization Algorithms 2025)

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28 pages, 4821 KiB

Open AccessArticle

A Novel Artificial Eagle-Inspired Optimization Algorithm for Trade Hub Location and Allocation Method

by Shuhan Hu, Gang Hu, Bo Du and Abdelazim G. Hussien

Biomimetics 2025, 10(8), 481; https://doi.org/10.3390/biomimetics10080481 - 22 Jul 2025

Abstract

Aiming for convenience and the low cost of goods transfer between towns, this paper proposes a trade hub location and allocation method based on a novel artificial eagle-inspired optimization algorithm. Firstly, the trade hub location and allocation model is established, taking the total [...] Read more.

Aiming for convenience and the low cost of goods transfer between towns, this paper proposes a trade hub location and allocation method based on a novel artificial eagle-inspired optimization algorithm. Firstly, the trade hub location and allocation model is established, taking the total cost consisting of construction and transportation costs as the objective function. Then, to solve the nonlinear model, a novel artificial eagle optimization algorithm (AEOA) is proposed by simulating the collective migration behaviors of artificial eagles when facing a severe living environment. Three main strategies are designed to help the algorithm effectively explore the decision space: the situational awareness and analysis stage, the free exploration stage, and the flight formation integration stage. In the first stage, artificial eagles are endowed with intelligent thinking, thus generating new positions closer to the optimum by perceiving the current situation and updating their positions. In the free exploration stage, artificial eagles update their positions by drawing on the current optimal position, ensuring more suitable habitats can be found. Meanwhile, inspired by the consciousness of teamwork, a formation flying method based on distance information is introduced in the last stage to improve stability and success rate. Test results from the CEC2022 suite indicate that the AEOA can obtain better solutions for 11 functions out of all 12 functions compared with 8 other popular algorithms. Faster convergence speed and stronger stability of the AEOA are also proved by quantitative analysis. Finally, the trade hub location and allocation method is proposed by combining the optimization model and the AEOA. By solving two typical simulated cases, this method can select suitable hubs with lower construction costs and achieve reasonable allocation between hubs and the rest of the towns to reduce transportation costs. Thus, it is used to solve the trade hub location and allocation problem of Henan province in China to help the government make sound decisions. Full article

(This article belongs to the Special Issue Nature-Inspired Metaheuristic Optimization Algorithms 2025)

18 pages, 2502 KiB

Open AccessArticle

Learning Local Texture and Global Frequency Clues for Face Forgery Detection

by Xin Jin, Yuru Kou, Yuhao Xie, Yuying Zhao, Miss Laiha Mat Kiah, Qian Jiang and Wei Zhou

Biomimetics 2025, 10(8), 480; https://doi.org/10.3390/biomimetics10080480 - 22 Jul 2025

Abstract

In recent years, the rapid advancement of deep learning techniques has significantly propelled the development of face forgery methods, drawing considerable attention to face forgery detection. However, existing detection methods still struggle with generalization across different datasets and forgery techniques. In this work, [...] Read more.

In recent years, the rapid advancement of deep learning techniques has significantly propelled the development of face forgery methods, drawing considerable attention to face forgery detection. However, existing detection methods still struggle with generalization across different datasets and forgery techniques. In this work, we address this challenge by leveraging both local texture cues and global frequency domain information in a complementary manner to enhance the robustness of face forgery detection. Specifically, we introduce a local texture mining and enhancement module. The input image is segmented into patches and a subset is strategically masked, then texture enhanced. This joint masking and enhancement strategy forces the model to focus on generalizable localized texture traces, mitigates overfitting to specific identity features and enabling the model to capture more meaningful subtle traces of forgery. Additionally, we extract multi-scale frequency domain features from the face image using wavelet transform, thereby preserving various frequency domain characteristics of the image. And we propose an innovative frequency-domain processing strategy to adjust the contributions of different frequency-domain components through frequency-domain selection and dynamic weighting. This Facilitates the model’s ability to uncover frequency-domain inconsistencies across various global frequency layers. Furthermore, we propose an integrated framework that combines these two feature modalities, enhanced with spatial attention and channel attention mechanisms, to foster a synergistic effect. Extensive experiments conducted on several benchmark datasets demonstrate that the proposed technique demonstrates superior performance and generalization capabilities compared to existing methods. Full article

(This article belongs to the Special Issue Exploration of Bioinspired Computer Vision and Pattern Recognition)

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12 pages, 5175 KiB

Open AccessArticle

Bioinspired Swimming Robots with 3D Biomimetic Shark Denticle Structures for Controlled Marangoni Propulsion

by Kang Yang, Chengming Wang, Lei Jiang, Ruochen Fang and Zhichao Dong

Biomimetics 2025, 10(8), 479; https://doi.org/10.3390/biomimetics10080479 - 22 Jul 2025

Abstract

Shark skin exhibits a well-defined multilayered architecture, consisting of three-dimensional denticles and an underlying dermal layer, which contributes to its passive drag reduction. However, the active drag reduction mechanisms of this interface remain largely unexplored. In this study, the Marangoni effect potentially arising [...] Read more.

Shark skin exhibits a well-defined multilayered architecture, consisting of three-dimensional denticles and an underlying dermal layer, which contributes to its passive drag reduction. However, the active drag reduction mechanisms of this interface remain largely unexplored. In this study, the Marangoni effect potentially arising from the active secretion of mucus on shark skin is investigated. A 3D-printed swimming robot with a porous substrate and a biomimetic shark denticle structure is developed. By introducing surfactants into the porous substrate and adjusting denticle arrangements, on-demand propulsion and controlled swimming trajectories are achieved. A superhydrophobic surface is fabricated on the swimming robot, which reduces water resistance and enhances propulsion. Moreover, denticles with a 30° attack angle demonstrate optimal propulsion performance in both Marangoni-driven hydrodynamics and aerodynamics. This study suggests that the secretion of mucus on shark skin may facilitate active drag reduction via the Marangoni effect, offering novel insights into the biomimetic structural design of autonomous swimming robots. Full article

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

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23 pages, 3554 KiB

Open AccessArticle

Multi-Sensor Fusion Framework for Reliable Localization and Trajectory Tracking of Mobile Robot by Integrating UWB, Odometry, and AHRS

by Quoc-Khai Tran and Young-Jae Ryoo

Biomimetics 2025, 10(7), 478; https://doi.org/10.3390/biomimetics10070478 - 21 Jul 2025

Abstract

This paper presents a multi-sensor fusion framework for the accurate indoor localization and trajectory tracking of a differential-drive mobile robot. The proposed system integrates Ultra-Wideband (UWB) trilateration, wheel odometry, and Attitude and Heading Reference System (AHRS) data using a Kalman filter. This fusion [...] Read more.

This paper presents a multi-sensor fusion framework for the accurate indoor localization and trajectory tracking of a differential-drive mobile robot. The proposed system integrates Ultra-Wideband (UWB) trilateration, wheel odometry, and Attitude and Heading Reference System (AHRS) data using a Kalman filter. This fusion approach reduces the impact of noisy and inaccurate UWB measurements while correcting odometry drift. The system combines raw UWB distance measurements with wheel encoder readings and heading information from an AHRS to improve robustness and positioning accuracy. Experimental validation was conducted through repeated closed-loop trajectory trials. The results demonstrate that the proposed method significantly outperforms UWB-only localization, yielding reduced noise, enhanced consistency, and lower Dynamic Time Warping (DTW) distances across repetitions. The findings confirm the system’s effectiveness and suitability for real-time mobile robot navigation in indoor environments. Full article

(This article belongs to the Special Issue Advanced Intelligent Systems and Biomimetics)

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38 pages, 9771 KiB

Open AccessArticle

Global Research Trends in Biomimetic Lattice Structures for Energy Absorption and Deformation: A Bibliometric Analysis (2020–2025)

by Sunny Narayan, Brahim Menacer, Muhammad Usman Kaisan, Joseph Samuel, Moaz Al-Lehaibi, Faisal O. Mahroogi and Víctor Tuninetti

Biomimetics 2025, 10(7), 477; https://doi.org/10.3390/biomimetics10070477 - 19 Jul 2025

Abstract

Biomimetic lattice structures, inspired by natural architectures such as bone, coral, mollusk shells, and Euplectella aspergillum, have gained increasing attention for their exceptional strength-to-weight ratios, energy absorption, and deformation control. These properties make them ideal for advanced engineering applications in aerospace, biomedical devices, [...] Read more.

Biomimetic lattice structures, inspired by natural architectures such as bone, coral, mollusk shells, and Euplectella aspergillum, have gained increasing attention for their exceptional strength-to-weight ratios, energy absorption, and deformation control. These properties make them ideal for advanced engineering applications in aerospace, biomedical devices, and structural impact protection. This study presents a comprehensive bibliometric analysis of global research on biomimetic lattice structures published between 2020 and 2025, aiming to identify thematic trends, collaboration patterns, and underexplored areas. A curated dataset of 3685 publications was extracted from databases like PubMed, Dimensions, Scopus, IEEE, Google Scholar, and Science Direct and merged together. After the removal of duplication and cleaning, about 2226 full research articles selected for the bibliometric analysis excluding review works, conference papers, book chapters, and notes using Cite space, VOS viewer version 1.6.20, and Bibliometrix R packages (4.5. 64-bit) for mapping co-authorship networks, institutional affiliations, keyword co-occurrence, and citation relationships. A significant increase in the number of publications was found over the past year, reflecting growing interest in this area. The results identify China as the most prolific contributor, with substantial institutional support and active collaboration networks, especially with European research groups. Key research focuses include additive manufacturing, finite element modeling, machine learning-based design optimization, and the performance evaluation of bioinspired geometries. Notably, the integration of artificial intelligence into structural modeling is accelerating a shift toward data-driven design frameworks. However, gaps remain in geometric modeling standardization, fatigue behavior analysis, and the real-world validation of lattice structures under complex loading conditions. This study provides a strategic overview of current research directions and offers guidance for future interdisciplinary exploration. The insights are intended to support researchers and practitioners in advancing next-generation biomimetic materials with superior mechanical performance and application-specific adaptability. Full article

(This article belongs to the Special Issue Nature-Inspired Science and Engineering for Sustainable Future)

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45 pages, 11380 KiB

Open AccessArticle

Application of Multi-Strategy Controlled Rime Algorithm in Path Planning for Delivery Robots

by Haokai Lv, Qian Qian, Jiawen Pan, Miao Song, Yong Feng and Yingna Li

Biomimetics 2025, 10(7), 476; https://doi.org/10.3390/biomimetics10070476 - 19 Jul 2025

Abstract

As a core component of automated logistics systems, delivery robots hold significant application value in the field of unmanned delivery. This research addresses the robot path planning problem, aiming to enhance delivery efficiency and reduce operational costs through systematic improvements to the RIME [...] Read more.

As a core component of automated logistics systems, delivery robots hold significant application value in the field of unmanned delivery. This research addresses the robot path planning problem, aiming to enhance delivery efficiency and reduce operational costs through systematic improvements to the RIME optimization algorithm. Through in-depth analysis, we identified several major drawbacks in the standard RIME algorithm for path planning: insufficient global exploration capability in the initial stages, a lack of diversity in the hard RIME search mechanism, and oscillatory phenomena in soft RIME step size adjustment. These issues often lead to undesirable phenomena in path planning, such as local optima traps, path redundancy, or unsmooth trajectories. To address these limitations, this study proposes the Multi-Strategy Controlled Rime Algorithm (MSRIME), whose innovation primarily manifests in three aspects: first, it constructs a multi-strategy collaborative optimization framework, utilizing an infinite folding Fuch chaotic map for intelligent population initialization to significantly enhance the diversity of solutions; second, it designs a cooperative mechanism between a controlled elite strategy and an adaptive search strategy that, through a dynamic control factor, autonomously adjusts the strategy activation probability and adaptation rate, expanding the search space while ensuring algorithmic convergence efficiency; and finally, it introduces a cosine annealing strategy to improve the step size adjustment mechanism, reducing parameter sensitivity and effectively preventing path distortions caused by abrupt step size changes. During the algorithm validation phase, comparative tests were conducted between two groups of algorithms, demonstrating their significant advantages in optimization capability, convergence speed, and stability. Further experimental analysis confirmed that the algorithm’s multi-strategy framework effectively suppresses the impact of coordinate and dimensional differences on path quality during iteration, making it more suitable for delivery robot path planning scenarios. Ultimately, path planning experimental results across various Building Coverage Rate (BCR) maps and diverse application scenarios show that MSRIME exhibits superior performance in key indicators such as path length, running time, and smoothness, providing novel technical insights and practical solutions for the interdisciplinary research between intelligent logistics and computer science. Full article

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

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18 pages, 4607 KiB

Open AccessArticle

Multi-Objective Machine Learning Optimization of Cylindrical TPMS Lattices for Bone Implants

by Mansoureh Rezapourian, Ali Cheloee Darabi, Mohammadreza Khoshbin and Irina Hussainova

Biomimetics 2025, 10(7), 475; https://doi.org/10.3390/biomimetics10070475 - 18 Jul 2025

Abstract

This study presents a multi-objective optimization framework for designing cylindrical triply periodic minimal surface (TPMS) lattices tailored for bone implant applications. Using an artificial neural network (ANN) as a surrogate model trained on simulated data, four key properties—ultimate stress (U), energy absorption (EA), [...] Read more.

This study presents a multi-objective optimization framework for designing cylindrical triply periodic minimal surface (TPMS) lattices tailored for bone implant applications. Using an artificial neural network (ANN) as a surrogate model trained on simulated data, four key properties—ultimate stress (U), energy absorption (EA), surface area-to-volume ratio (SA/VR), and relative density (RD)—were predicted from seven lattice design parameters. To address anatomical variability, a novel implant size-based categorization (small, medium, and large) was introduced, and separate optimization runs were conducted for each group. The optimization was performed via the NSGA-II algorithm to maximize mechanical performance (U and EA) and surface efficiency (SA/VR), while filtering for biologically relevant RD values (20–40%). Separate optimization runs were conducted for small, medium, and large implant size groups. A total of 105 Pareto-optimal designs were identified, with 75 designs retained after RD filtering. SHapley Additive exPlanations (SHAP) analysis revealed the dominant influence of thickness and unit cell size on target properties. Kernel density and boxplot comparisons confirmed distinct performance trends across size groups. The framework effectively balances competing design goals and enables the selection of size-specific lattices. The proposed approach provides a reproducible pathway for optimizing bioarchitectures, with the potential to accelerate the development of lattice-based implants in personalized medicine. Full article

(This article belongs to the Special Issue Biomimicry and Functional Materials: 5th Edition)

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17 pages, 3302 KiB

Open AccessArticle

Effects of Ovariectomy and Low-Calcium Diet on Six Different Sites of the Rat Skeleton

by Xanthippi Dereka, Rodopi Emfietzoglou and Pavlos Lelovas

Biomimetics 2025, 10(7), 474; https://doi.org/10.3390/biomimetics10070474 - 18 Jul 2025

Abstract

The aim of this study was to evaluate structural and micro-architectural changes in the mandible, parietal bone, femur, and tibia in OVX rats at different time periods after ovariectomy. Forty-two 11-month-old female Wistar rats were used. Six rats without surgery were euthanized to [...] Read more.

The aim of this study was to evaluate structural and micro-architectural changes in the mandible, parietal bone, femur, and tibia in OVX rats at different time periods after ovariectomy. Forty-two 11-month-old female Wistar rats were used. Six rats without surgery were euthanized to serve as a baseline. Eighteen rats were ovariectomized and fed with a calcium-deficient diet, and eighteen animals were used as controls (Ctrls) and fed with a standard diet. Six OVX rats and six Ctrls were euthanized at 3, 6, and 9 months. Qualitative histology and dual-energy X-ray absorptiometry (DXA) were performed. Histological evaluation of bones harvested from the OVX groups revealed trabecular bone reduction, while no significant differences in the cortical bone of OVX and Ctrls were observed. DXA measurements of (1) femoral diaphysis showed a significant decrease in the OVX group compared to the Ctrl groups at 3 (p = 0.041), 6 (p < 0.001), and 9 months (p < 0.001); (2) the proximal tibia showed a significant decrease in the OVX group compared to the Ctrl groups (p < 0.001); (3) parietal bone showed a significant difference between OVX and Ctrls at 6 months (p = 0.012); and (4) the mandible showed no significant differences between the OVX and Ctrl groups. OVX aged rats might present reductions in the density of the femoral diaphysis, proximal tibia, parietal bone, and mandible at different time points. These findings contribute to the field of biomimetics by providing more details for the understanding of age- and hormone-related bone changes in the osteoporotic-like rat model. Such data are critical for the development of biomimetic materials and structures that attempt to simulate natural bone adaptation and deterioration, especially in the context of postmenopausal or osteoporotic conditions. Full article

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

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17 pages, 6781 KiB

Open AccessArticle

Fish Scale-Inspired Flow Control for Corner Vortex Suppression in Compressor Cascades

by Jin-Long Shen, Ho-Chun Yang and Szu-I Yeh

Biomimetics 2025, 10(7), 473; https://doi.org/10.3390/biomimetics10070473 - 18 Jul 2025

Abstract

Corner separation at the junction of blade surfaces and end walls remains a significant challenge in compressor cascade performance. This study proposes a passive flow control strategy inspired by the geometric arrangement of biological fish scales to address this issue. A fish scale-like [...] Read more.

Corner separation at the junction of blade surfaces and end walls remains a significant challenge in compressor cascade performance. This study proposes a passive flow control strategy inspired by the geometric arrangement of biological fish scales to address this issue. A fish scale-like surface structure was applied to the suction side of a cascade blade to reduce viscous drag and modulate secondary flow behavior. Wind tunnel experiments and numerical simulations were conducted to evaluate its aerodynamic effects. The results show that the fish scale-inspired configuration induced climbing vortices that energized low-momentum fluid near the end wall, effectively suppressing both passage and corner vortices. This led to a reduction in spanwise flow penetration and a decrease in total pressure loss of up to 5.69%. The enhanced control of secondary flows also contributed to improved flow uniformity in the end-wall region. These findings highlight the potential of biologically inspired surface designs for corner vortex suppression and aerodynamic efficiency improvement in turbomachinery systems. Full article

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

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26 pages, 5344 KiB

Open AccessArticle

Sliding Mode Repetitive Control Based on the Unknown Dynamics Estimator of a Two-Stage Supply Pressure Hydraulic Hexapod Robot

by Ziqi Liu, Bo Jin, Junkui Dong, Qingyun Yao, Yinglian Jin, Tao Liu and Binrui Wang

Biomimetics 2025, 10(7), 472; https://doi.org/10.3390/biomimetics10070472 - 18 Jul 2025

Abstract

Hydraulic actuated legged robots display bright prospects and significant research value in areas such as unmanned area surveying, disaster rescue, military fields, and other scenarios owing to their excellent bionic characteristics, particularly their heavy payload capabilities and high power density. To realize the [...] Read more.

Hydraulic actuated legged robots display bright prospects and significant research value in areas such as unmanned area surveying, disaster rescue, military fields, and other scenarios owing to their excellent bionic characteristics, particularly their heavy payload capabilities and high power density. To realize the all-terrain adaptation locomotion of the hydraulic hexapod robot (HHR) with a heavy payload, one alternative control framework is position–posture control based on joint position control. As the foundation for the steady locomotion of HHRs, it is imperative to realize high-precision joint position control to improve the robustness under external disturbances during the walking process and to complete the attitude control task. To address the above issues, this paper proposes a sliding mode repetitive control based on the unknown dynamics estimator (SMRC + UDE) for the knee and hip joints of the HHR with a two-stage supply pressure hydraulic system (TSS). The effectiveness of the SMRC + UDE method is verified using a simulation environment and the ZJUHEX01 prototype experimental platform, and it is compared with the results for PID and adaptive robust sliding mode control (ARSMC). The results show that SMRC + UDE may be more suitable for our HHR, considering both the control performance and efficiency factors. Full article

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49 pages, 7424 KiB

Open AccessArticle

ACIVY: An Enhanced IVY Optimization Algorithm with Adaptive Cross Strategies for Complex Engineering Design and UAV Navigation

by Heming Jia, Mahmoud Abdel-salam and Gang Hu

Biomimetics 2025, 10(7), 471; https://doi.org/10.3390/biomimetics10070471 - 17 Jul 2025

Abstract

The Adaptive Cross Ivy (ACIVY) algorithm is a novel bio-inspired metaheuristic that emulates ivy plant growth behaviors for complex optimization problems. While the original Ivy Optimization Algorithm (IVYA) demonstrates a competitive performance, it suffers from limited inter-individual information exchange, inadequate directional guidance for [...] Read more.

The Adaptive Cross Ivy (ACIVY) algorithm is a novel bio-inspired metaheuristic that emulates ivy plant growth behaviors for complex optimization problems. While the original Ivy Optimization Algorithm (IVYA) demonstrates a competitive performance, it suffers from limited inter-individual information exchange, inadequate directional guidance for local optima escape, and abrupt exploration–exploitation transitions. To address these limitations, ACIVY integrates three strategic enhancements: the crisscross strategy, enabling horizontal and vertical crossover operations for improved population diversity; the LightTrack strategy, incorporating positional memory and repulsion mechanisms for effective local optima escape; and the Top-Guided Adaptive Mutation strategy, implementing ranking-based mutation with dynamic selection pools for smooth exploration–exploitation balance. Comprehensive evaluations on the CEC2017 and CEC2022 benchmark suites demonstrate ACIVY’s superior performance against state-of-the-art algorithms across unimodal, multimodal, hybrid, and composite functions. ACIVY achieved outstanding average rankings of 1.25 (CEC2022) and 1.41 (CEC2017 50D), with statistical significance confirmed through Wilcoxon tests. Practical applications in engineering design optimization and UAV path planning further validate ACIVY’s robust performance, consistently delivering optimal solutions across diverse real-world scenarios. The algorithm’s exceptional convergence precision, solution reliability, and computational efficiency establish it as a powerful tool for challenging optimization problems requiring both accuracy and consistency. Full article

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

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33 pages, 5578 KiB

Open AccessReview

Underwater Drag Reduction Applications and Fabrication of Bio-Inspired Surfaces: A Review

by Zaixiang Zheng, Xin Gu, Shengnan Yang, Yue Wang, Ying Zhang, Qingzhen Han and Pan Cao

Biomimetics 2025, 10(7), 470; https://doi.org/10.3390/biomimetics10070470 - 17 Jul 2025

Abstract

As an emerging energy-saving approach, bio-inspired drag reduction technology has become a key research direction for reducing energy consumption and greenhouse gas emissions. This study introduces the latest research progress on bio-inspired microstructured surfaces in the field of underwater drag reduction, focusing on [...] Read more.

As an emerging energy-saving approach, bio-inspired drag reduction technology has become a key research direction for reducing energy consumption and greenhouse gas emissions. This study introduces the latest research progress on bio-inspired microstructured surfaces in the field of underwater drag reduction, focusing on analyzing the drag reduction mechanism, preparation process, and application effect of the three major technological paths; namely, bio-inspired non-smooth surfaces, bio-inspired superhydrophobic surfaces, and bio-inspired modified coatings. Bio-inspired non-smooth surfaces can significantly reduce the wall shear stress by regulating the flow characteristics of the turbulent boundary layer through microstructure design. Bio-inspired superhydrophobic surfaces form stable gas–liquid interfaces through the construction of micro-nanostructures and reduce frictional resistance by utilizing the slip boundary effect. Bio-inspired modified coatings, on the other hand, realize the synergistic function of drag reduction and antifouling through targeted chemical modification of materials and design of micro-nanostructures. Although these technologies have made significant progress in drag reduction performance, their engineering applications still face bottlenecks such as manufacturing process complexity, gas layer stability, and durability. Future research should focus on the analysis of drag reduction mechanisms and optimization of material properties under multi-physical field coupling conditions, the development of efficient and low-cost manufacturing processes, and the enhancement of surface stability and adaptability through dynamic self-healing coatings and smart response materials. It is hoped that the latest research status of bio-inspired drag reduction technology reviewed in this study provides a theoretical basis and technical reference for the sustainable development and energy-saving design of ships and underwater vehicles. Full article

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