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Biomimetics

Biomimetics is an international, peer-reviewed, open access journal on biomimicry and bionics, published monthly online by MDPI. The International Society of Bionic Engineering (ISBE) is affiliated with Biomimetics.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Ei Compendex, CAPlus / SciFinder, and other databases.
Journal Rank: JCR - Q1 (Engineering, Multidisciplinary) / CiteScore - Q2 (Biomedical Engineering)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.1 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.

Impact Factor: 3.9 (2024); 5-Year Impact Factor: 4.0 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2313-7673

Latest Articles

57 pages, 12253 KB

Open AccessArticle

Graduate Student Evolutionary Algorithm: A Novel Metaheuristic Algorithm for 3D UAV and Robot Path Planning

by Xiaoxuan Liu, Shaobo Li, Yongming Wu and Zijun Fu

Biomimetics 2025, 10(9), 616; https://doi.org/10.3390/biomimetics10090616 - 12 Sep 2025

In recent years, numerical optimization, UAVs, and robot path planning have become hot research topics. Solving these fundamental artificial intelligence problems is crucial for further advancements. However, traditional methods struggle with complex nonlinear problems, prompting researchers to explore intelligent optimization algorithms. Existing approaches, [...] Read more.

In recent years, numerical optimization, UAVs, and robot path planning have become hot research topics. Solving these fundamental artificial intelligence problems is crucial for further advancements. However, traditional methods struggle with complex nonlinear problems, prompting researchers to explore intelligent optimization algorithms. Existing approaches, however, still suffer from slow convergence, low accuracy, and poor robustness. Inspired by graduate students’ daily behavior, this paper proposes a novel intelligent optimization algorithm, the Graduate Student Evolutionary Algorithm (GSEA). By simulating key processes such as searching for research directions and concentrating on studies, a mathematical model of GSEA is established. The algorithm’s convergence behavior is analyzed qualitatively, and its performance is evaluated against competitive algorithms on the CEC2017 and CEC2022 test sets. Statistical tests confirm GSEA’s effectiveness and robustness. To further validate its practical applicability, GSEA is applied to UAV and robot path planning problems, with experimental results demonstrating its superiority in solving real-world optimization challenges. Full article

(This article belongs to the Special Issue Advances in Swarm Intelligence Optimization Algorithms and Applications: 2nd Edition)

17 pages, 3353 KB

Open AccessArticle

Design and Machine Learning Modeling of a Multi-Degree-of-Freedom Bionic Pneumatic Soft Actuator

by Yu Zhang, Linghui Peng, Wenchuan Zhao, Ning Wang and Zheng Zhang

Biomimetics 2025, 10(9), 615; https://doi.org/10.3390/biomimetics10090615 - 12 Sep 2025

A novel multi-degree-of-freedom bionic Soft Pneumatic Actuator (SPA) inspired by the shoulder joint of a sea turtle is proposed. The SPA is mainly composed of a combination of oblique chamber actuator units capable of omnidirectional bending and bi-directional twisting, which can restore the [...] Read more.

A novel multi-degree-of-freedom bionic Soft Pneumatic Actuator (SPA) inspired by the shoulder joint of a sea turtle is proposed. The SPA is mainly composed of a combination of oblique chamber actuator units capable of omnidirectional bending and bi-directional twisting, which can restore the multi-modal motions of a sea turtle’s flipper limb in three-dimensional space. To address the nonlinear behavior of the complex structure of SPA, traditional modeling is difficult. The attitude information of each axis of the actuator is extracted in real time using a high-precision Inertial Measurement Unit (IMU), and the attitude outputs of the SPA are modeled using six machine learning methods. The results show that the XGBoost model performs best in attitude modeling. Its R² can reach 0.974, and the average absolute errors of angles in Roll, Pitch, and Yaw axes are 1.315°, 1.543°, and 1.048°, respectively. The multi-axis attitude of the SPA can be predicted with high accuracy in real time. The studies on deformation capability, actuation output performance, and underwater validation experiments demonstrate that the SPA meets the bionic sea turtle shoulder joint requirements. This study provides a new theoretical foundation and technical path for the development, control, and bionic application of complex multi-degree-of-freedom SPA systems. Full article

(This article belongs to the Special Issue Bioinspired Structures for Soft Actuators: 2nd Edition)

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18 pages, 15272 KB

Open AccessArticle

IDP-Head: An Interactive Dual-Perception Architecture for Organoid Detection in Mouse Microscopic Images

by Yuhang Yang, Changyuan Fan, Xi Zhou and Peiyang Wei

Biomimetics 2025, 10(9), 614; https://doi.org/10.3390/biomimetics10090614 - 11 Sep 2025

The widespread application of organoids in disease modeling and drug development is significantly constrained by challenges in automated quantitative analysis. In bright-field microscopy images, organoids exhibit complex characteristics, including irregular morphology, blurred boundaries, and substantial scale variations, largely stemming from their dynamic self-organization [...] Read more.

The widespread application of organoids in disease modeling and drug development is significantly constrained by challenges in automated quantitative analysis. In bright-field microscopy images, organoids exhibit complex characteristics, including irregular morphology, blurred boundaries, and substantial scale variations, largely stemming from their dynamic self-organization that mimics in vivo tissue development. Existing convolutional neural network-based methods are limited by fixed receptive fields and insufficient modeling of inter-channel relationships, making them inadequate for detecting such evolving biological structures. To address these challenges, we propose a novel detection head, termed Interactive Dual-Perception Head (IDP-Head), inspired by hierarchical perception mechanisms in the biological visual cortex. Integrated into the RTMDet framework, IDP-Head comprises two bio-inspired components: a Large-Kernel Global Perception Module (LGPM) to capture global morphological dependencies, analogous to the wide receptive fields of cortical neurons, and a Progressive Channel Synergy Module (PCSM) that models inter-channel semantic collaboration, echoing the integrative processing of multi-channel stimuli in neural systems. Additionally, we construct a new organoid detection dataset to mitigate the scarcity of annotated data. Extensive experiments on both our dataset and public benchmarks demonstrate that IDP-Head achieves a 5-percentage-point improvement in mean Average Precision (mAP) over the baseline model, offering a biologically inspired and effective solution for high-fidelity organoid detection. Full article

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

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31 pages, 1863 KB

Open AccessArticle

Human Activity Recognition with Noise-Injected Time-Distributed AlexNet

by Sanjay Dutta, Tossapon Boongoen and Reyer Zwiggelaar

Biomimetics 2025, 10(9), 613; https://doi.org/10.3390/biomimetics10090613 - 11 Sep 2025

This study investigates the integration of biologically inspired noise injection with a time-distributed adaptation of the AlexNet architecture to enhance the performance and robustness of human activity recognition (HAR) systems. It is a critical field in computer vision which involves identifying and interpreting [...] Read more.

This study investigates the integration of biologically inspired noise injection with a time-distributed adaptation of the AlexNet architecture to enhance the performance and robustness of human activity recognition (HAR) systems. It is a critical field in computer vision which involves identifying and interpreting human actions from video sequences and has applications in healthcare, security and smart environments. The proposed model is based on an adaptation of AlexNet, originally developed for static image classification and not inherently suited for modelling temporal sequences for video action classification tasks. While our time-distributed AlexNet efficiently captures spatial and temporal features and suitable for video classification. However, its performance can be limited by overfitting and poor generalisation to unseen scenarios, to address these challenges, Gaussian noise was introduced at the input level during training, inspired by neural mechanisms observed in biological sensory processing to handle variability and uncertainty. Experiments were conducted on the EduNet, UCF50 and UCF101 datasets. The EduNet dataset was specifically designed for educational environments and we evaluate the impact of noise injection on model accuracy, stability and overall performance. The proposed bio-inspired noise-injected time-distributed AlexNet achieved an overall accuracy of 91.40% and an F1 score of 92.77%, outperforming other state-of-the-art models. Hyperparameter tuning, particularly optimising the learning rate, further enhanced model stability, reflected in lower standard deviation values across multiple experimental runs. These findings demonstrate that the strategic combination of noise injection with time-distributed architectures improves generalisation and robustness in HAR, paving the way for resource-efficient and real-world-deployable deep learning systems. Full article

(This article belongs to the Section Bioinspired Sensorics, Information Processing and Control)

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51 pages, 10350 KB

Open AccessArticle

An Improved Greater Cane Rat Algorithm with Adaptive and Global-Guided Mechanisms for Solving Real-World Engineering Problems

by Yepei Chen, Zhangzhi Tian, Kaifan Zhang, Feng Zhao and Aiping Zhao

Biomimetics 2025, 10(9), 612; https://doi.org/10.3390/biomimetics10090612 - 10 Sep 2025

This study presents an improved variant of the greater cane rat algorithm (GCRA), called adaptive and global-guided greater cane rat algorithm (AGG-GCRA), which aims to alleviate some key limitations of the original GCRA regarding convergence speed, solution precision, and stability. GCRA simulates the [...] Read more.

This study presents an improved variant of the greater cane rat algorithm (GCRA), called adaptive and global-guided greater cane rat algorithm (AGG-GCRA), which aims to alleviate some key limitations of the original GCRA regarding convergence speed, solution precision, and stability. GCRA simulates the foraging behavior of the greater cane rat during both mating and non-mating seasons, demonstrating intelligent exploration capabilities. However, the original algorithm still faces challenges such as premature convergence and inadequate local exploitation when applied to complex optimization problems. To address these issues, this paper introduces four key improvements to the GCRA: (1) a global optimum guidance term to enhance the convergence directionality; (2) a flexible parameter adjustment system designed to maintain a dynamic balance between exploration and exploitation; (3) a mechanism for retaining top-quality solutions to ensure the preservation of optimal results.; and (4) a local perturbation mechanism to help escape local optima. To comprehensively evaluate the optimization performance of AGG-GCRA, 20 separate experiments were carried out across 26 standard benchmark functions and six real-world engineering optimization problems, with comparisons made against 11 advanced metaheuristic optimization methods. The findings indicate that AGG-GCRA surpasses the competing algorithms in aspects of convergence rate, solution precision, and robustness. In the stability analysis, AGG-GCRA consistently obtained the global optimal solution in multiple runs for five engineering cases, achieving an average rank of first place and a standard deviation close to zero, highlighting its exceptional global search capabilities and excellent repeatability. Statistical tests, including the Friedman ranking and Wilcoxon signed-rank tests, provide additional validation for the effectiveness and importance of the proposed algorithm. In conclusion, AGG-GCRA provides an efficient and stable intelligent optimization tool for solving various optimization problems. Full article

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23 pages, 4045 KB

Open AccessArticle

Advanced Robust Heading Control for Unmanned Surface Vessels Using Hybrid Metaheuristic-Optimized Variable Universe Fuzzy PID with Enhanced Smith Predictor

by Siyu Zhan, Qiang Liu, Zhao Zhao, Shen’ao Zhang and Yaning Xu

Biomimetics 2025, 10(9), 611; https://doi.org/10.3390/biomimetics10090611 - 10 Sep 2025

With the increasing deployment of unmanned surface vessels (USVs) in complex marine operations such as ocean monitoring, search and rescue, and military reconnaissance, precise heading control under environmental disturbances and system delays has become a critical challenge. This paper presents an advanced robust [...] Read more.

With the increasing deployment of unmanned surface vessels (USVs) in complex marine operations such as ocean monitoring, search and rescue, and military reconnaissance, precise heading control under environmental disturbances and system delays has become a critical challenge. This paper presents an advanced robust heading control strategy for USVs operating under these demanding conditions. The proposed approach integrates three key innovations: (1) an enhanced Smith predictor for accurate time-delay compensation, (2) a variable-universe fuzzy PID controller with self-adaptive scaling domains that dynamically adjust to error magnitude and rate of change, and (3) a hybrid metaheuristic optimization algorithm combining beetle antennae search, harmony search, and genetic algorithm (BAS-HSA-GA) for optimal parameter tuning. Through comprehensive simulations using a Nomoto first-order time-delay model under combined white noise and second-order wave disturbances, the system demonstrates superior performance with over 90% reduction in steady-state heading error and ≈30% faster settling time compared to conventional PID and single-optimization fuzzy PID methods. Field trials under sea-state 4 conditions confirm 15–25% lower tracking error in realistic operating scenarios. The controller’s stability is rigorously verified through Lyapunov analysis, while comparative studies show significant improvements in S-shaped path tracking performance, achieving better IAE/ITAE metrics than DRL, ANFC, and ACO approaches. This work provides a comprehensive solution for high-precision, delay-resilient USV heading control in dynamic marine environments. Full article

(This article belongs to the Section Bioinspired Sensorics, Information Processing and Control)

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23 pages, 1998 KB

Open AccessArticle

Hybrid Cuckoo Search–Bees Algorithm with Memristive Chaotic Initialization for Cryptographically Strong S-Box Generation

by Sinem Akyol

Biomimetics 2025, 10(9), 610; https://doi.org/10.3390/biomimetics10090610 - 10 Sep 2025

One of the essential parts of contemporary cryptographic systems is s-boxes (Substitution Boxes), which give encryption algorithms more complexity and resilience due to their nonlinear structure. In this study, we propose CSBA (Cuckoo Search–Bees Algorithm), a hybrid evolutionary method that combines the strengths [...] Read more.

One of the essential parts of contemporary cryptographic systems is s-boxes (Substitution Boxes), which give encryption algorithms more complexity and resilience due to their nonlinear structure. In this study, we propose CSBA (Cuckoo Search–Bees Algorithm), a hybrid evolutionary method that combines the strengths of Cuckoo Search and Bees algorithms, to generate s-box structures with strong cryptographic properties. The initial population is generated with a high-diversity four-dimensional Memristive Lu chaotic map, taking advantage of the random yet deterministic nature of chaotic systems. This proposed method was designed with inspiration from biological systems. It was developed based on the foraging strategies of bees and the reproductive strategies of cuckoos. This nature-inspired structure enables an efficient scanning of the solution space. The resultant s-boxes’ fitness was assessed using the nonlinearity value. These s-boxes were then optimized using the hybrid CSBA algorithm suggested in this paper as well as the Bees algorithm. The performance of the proposed approaches was measured using SAC, nonlinearity, BIC-SAC, BIC-NL, maximum difference distribution, and linear uniformity (LU) metrics. Compared to other studies in the literature that used metaheuristic algorithms to generate s-boxes, the proposed approach demonstrates good performance. In particular, the average value of 109.75 obtained for the nonlinearity metric demonstrates high success. Therefore, this study demonstrates that robust and reliable s-boxes can be generated for symmetric encryption algorithms using the developed metaheuristic algorithms. Full article

(This article belongs to the Special Issue Biomimicry for Optimization, Control, and Automation: 3rd Edition)

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17 pages, 2861 KB

Open AccessArticle

High-Accuracy Lower-Limb Intent Recognition: A KPCA-ISSA-SVM Approach with sEMG-IMU Sensor Fusion

by Kaiyang Yin, Pengchao Hao, Huanli Zhao, Pengyu Lou and Yi Chen

Biomimetics 2025, 10(9), 609; https://doi.org/10.3390/biomimetics10090609 - 10 Sep 2025

Accurately decoding human locomotion intention from physiological signals remains a significant hurdle for the seamless control of advanced rehabilitation devices like exoskeletons and intelligent prosthetics. Conventional recognition methods often falter, exhibiting limited accuracy and struggling to capture the complex, nonlinear dynamics inherent in [...] Read more.

Accurately decoding human locomotion intention from physiological signals remains a significant hurdle for the seamless control of advanced rehabilitation devices like exoskeletons and intelligent prosthetics. Conventional recognition methods often falter, exhibiting limited accuracy and struggling to capture the complex, nonlinear dynamics inherent in biological data streams. Addressing these critical limitations, this study introduces a novel framework for lower-limb motion intent recognition, integrating Kernel Principal Component Analysis (KPCA) with a Support Vector Machine (SVM) optimized via an Improved Sparrow Search Algorithm (ISSA). Our approach commences by constructing a comprehensive high-dimensional feature space from synchronized surface electromyography (sEMG) and inertial measurement unit (IMU) data—a potent combination reflecting both muscle activation and limb kinematics. Critically, KPCA is employed for nonlinear dimensionality reduction; leveraging the power of kernel functions, it transcends the linear constraints of traditional PCA to extract low-dimensional principal components that retain significantly more discriminative information. Furthermore, the Sparrow Search Algorithm (SSA) undergoes three strategic enhancements: chaotic opposition-based learning for superior population diversity, adaptive dynamic weighting to adeptly balance exploration and exploitation, and hybrid mutation strategies to effectively mitigate premature convergence. This enhanced ISSA meticulously optimizes the SVM hyperparameters, ensuring robust classification performance. Experimental validation, conducted on a challenging 13-class lower-limb motion dataset, compellingly demonstrates the superiority of the proposed KPCA-ISSA-SVM architecture. It achieves a remarkable recognition accuracy of 95.35% offline and 93.3% online, substantially outperforming conventional PCA-SVM (91.85%) and standalone SVM (89.76%) benchmarks. This work provides a robust and significantly more accurate solution for intention perception in human–machine systems, paving the way for more intuitive and effective rehabilitation technologies by adeptly handling the nonlinear coupling characteristics of sEMG-IMU data and complex motion patterns. Full article

(This article belongs to the Special Issue Data-Centric Engineering for Sustainable Future with AI and Human-in-the-Loop)

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19 pages, 9017 KB

Open AccessArticle

Collagen Formulation in Xenogeneic Bone Substitutes Influences Cellular Responses in Periodontal Regeneration: An In Vitro Study

by Priscilla Pelaez-Cruz, Pia López Jornet and Eduardo Pons-Fuster

Biomimetics 2025, 10(9), 608; https://doi.org/10.3390/biomimetics10090608 - 10 Sep 2025

Background: Bone regeneration is a key therapeutic objective in periodontology, particularly in the treatment of alveolar defects caused by periodontal disease, dentoalveolar trauma, or surgical interventions. Among current regenerative strategies, collagen-enriched biomaterials have demonstrated an active role in modulating cellular behavior during bone [...] Read more.

Background: Bone regeneration is a key therapeutic objective in periodontology, particularly in the treatment of alveolar defects caused by periodontal disease, dentoalveolar trauma, or surgical interventions. Among current regenerative strategies, collagen-enriched biomaterials have demonstrated an active role in modulating cellular behavior during bone repair. However, the specific effects of different collagen formulations on human dental pulp stem cells (hDPSCs) have not yet been fully characterized. Objective: To evaluate the impact of xenogeneic bone grafts with and without collagen—OsteoBiol^® Gen-Os^® (GO), OsteoBiol^® GTO^® (GTO), and Geistlich Bio-Oss^® (BO)—on cell viability, adhesion, migration, osteogenic differentiation, and mineralization potential of hDPSCs, and to explore the molecular mechanisms underlying their effects. Methods: In vitro assays were conducted to assess viability (MTT and fluorescence staining), adhesion (SEM), migration (wound healing assay), and mineralization (Alizarin Red S staining). Gene expression analyses (RT-qPCR) were performed for adhesion/migration markers (FN, SDF-1, COL1A1), angiogenic/proliferation markers (VEGF, FGF2), and osteogenic differentiation markers (RUNX2, ALP, COL1A1). Results: GO showed a higher early expression of genes associated with adhesion, migration, angiogenesis (FN, SDF-1, VEGF and FGF2: p < 0.05; COL1A1: p < 0.01), and osteogenic differentiation (7 days: COL1A1 and ALP (p < 0.001)); (14 days: RUNX2, ALP: p < 0.001; COL1A1: p < 0.05), indicating a sequential activation of molecular pathways and mineralization capacity comparable to the control group. GTO demonstrated the best biocompatibility, with significantly higher cell viability (p < 0.05), strong adhesion, and markedly increased mineralization at 21 days (p < 0.001), despite moderate early gene expression. BO showed reduced cell viability at 10 mg/mL (p < 0.05) and 20 mg/mL (p < 0.001), with mineralization levels similar to the control group. Conclusion: Collagen-based xenografts demonstrate favorable interactions with hDPSCs, enhancing viability and promoting osteogenic differentiation. Our findings suggest that beyond the presence of collagen, the specific formulation of these biomaterials may modulate their biological performance, highlighting the importance of material design in optimizing regenerative outcomes. Clinical Significance: The formulation of collagen in xenogeneic bone substitutes may be a determining factor in enhancing periodontal regenerative outcomes by modulating the early cellular response and osteogenic activity in stem cell-based tissue engineering. Full article

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

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18 pages, 4937 KB

Open AccessArticle

Cam-Based Simple Design of Constant-Force Suspension Backpack to Isolate Dynamic Load

by Haotian Ju, Zihang Guan, Junchen Liu, Yao Huang, Kerui Sun, Lele Li, Weimao Wang, Tianjiao Zheng, Quan Xiong, Jie Zhao and Yanhe Zhu

Biomimetics 2025, 10(9), 607; https://doi.org/10.3390/biomimetics10090607 - 10 Sep 2025

Prolonged load carriage with ordinary backpacks (OBs) can cause muscle fatigue and skeletal injuries. Research indicates that suspended backpacks can effectively reduce energy expenditure; however, existing elastic rope-based suspension backpacks struggle to adapt to different speeds, while active suspension backpacks gain significant additional [...] Read more.

Prolonged load carriage with ordinary backpacks (OBs) can cause muscle fatigue and skeletal injuries. Research indicates that suspended backpacks can effectively reduce energy expenditure; however, existing elastic rope-based suspension backpacks struggle to adapt to different speeds, while active suspension backpacks gain significant additional weight due to the incorporated motors and batteries. This paper presents a novel cam-based constant-force suspension backpack (CCSB). The CCSB employs a cam–spring mechanism with near-zero suspension stiffness to minimize the inertial forces generated by load oscillations. A test platform was constructed to evaluate the constant-force performance of the mechanism, showing a maximum error of less than 1.96%. Load-carrying experiments were conducted at different walking speeds. Laboratory test results show that, compared with OBs, the CCSB reduces peak accelerative vertical force by an average of 84.47% and reduces human metabolic costs by 10.58%. Outdoor tests show that the CCSB can reduce transportation consumption by 8.26%. The CCSB’s compact structure makes it more suitable for commercialization and demonstrates significant potential for practical applications. Full article

(This article belongs to the Special Issue Bionic Technology—Robotic Exoskeletons and Prostheses: 3rd Edition)

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17 pages, 4687 KB

Open AccessArticle

Non-Bactericidal Antifouling Coating Inspired by the “Swinging Effect” of Coral Tentacles in Waves

by Yue Yin, Jianfu Wang and Xu Zheng

Biomimetics 2025, 10(9), 606; https://doi.org/10.3390/biomimetics10090606 - 10 Sep 2025

Inspired by the free swing of coral tentacles driven by water currents to actively repel microbial attachment, we have identified a unique physical anti-fouling strategy: coral “swinging effect” anti-fouling. Taking the fleshy soft coral (Sarcophyton trocheliophorum) as an example, its surface [...] Read more.

Inspired by the free swing of coral tentacles driven by water currents to actively repel microbial attachment, we have identified a unique physical anti-fouling strategy: coral “swinging effect” anti-fouling. Taking the fleshy soft coral (Sarcophyton trocheliophorum) as an example, its surface is covered with numerous soft tentacles. These coral tentacles utilize the force of water current fluctuations to freely sway, resembling a “feather duster” waving to repel microorganisms attempting to settle and establish themselves. Based on this characteristic, this study delves into the living habits of corals, observing the expansion and contraction cycles of their tentacles. Simultaneously, simulations of the anti-fouling performance of coral tentacles were conducted. It demonstrates that the “swinging effect” of the tentacles can effectively prevent the attachment of fouling organisms. Furthermore, this study uses S. trocheliophorum as a biomimetic prototype to design and prepare an artificial coral-mimic substrate (ACMS). It employs the common marine Gram-negative bacterium Paracoccus pantotrophus as a microbial sample to test anti-fouling performance in both pure static water environments and low-flow water environments. The results showed that the 13 mm-long ACMS could bend and overlap the surface of the rear tentacles to the greatest extent under the unidirectional scouring action of low-speed water flow (3.5 m/s), forming an anti-fouling protective layer. Additionally, the “swinging effect” phenomenon generated by the tentacles under water flow scouring demonstrated excellent anti-fouling effects. This study not only provides further evidence for research on coral antifouling performance but also offers new concepts and ideas for antifouling strategies in low-flow water environments, such as stationary ships in ports and underwater infrastructure facilities at docks. Full article

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

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30 pages, 3177 KB

Open AccessArticle

A Concept for Bio-Agentic Visual Communication: Bridging Swarm Intelligence with Biological Analogues

by Bryan Starbuck, Hanlong Li, Bryan Cochran, Marc Weissburg and Bert Bras

Biomimetics 2025, 10(9), 605; https://doi.org/10.3390/biomimetics10090605 - 9 Sep 2025

Biological swarms communicate through decentralized, adaptive behaviors shaped by local interactions, selective attention, and symbolic signaling. These principles of animal communication enable robust coordination without centralized control or persistent connectivity. This work presents a proof of concept that identifies, evaluates, and translates biological [...] Read more.

Biological swarms communicate through decentralized, adaptive behaviors shaped by local interactions, selective attention, and symbolic signaling. These principles of animal communication enable robust coordination without centralized control or persistent connectivity. This work presents a proof of concept that identifies, evaluates, and translates biological communication strategies into a generative visual language for unmanned aerial vehicle (UAV) swarm agents operating in radio-frequency (RF)-denied environments. Drawing from natural exemplars such as bee waggle dancing, white-tailed deer flagging, and peacock feather displays, we construct a configuration space that encodes visual messages through trajectories and LED patterns. A large language model (LLM), preconditioned using retrieval-augmented generation (RAG), serves as a generative translation layer that interprets perception data and produces symbolic UAV responses. Five test cases evaluate the system’s ability to preserve and adapt signal meaning through within-modality fidelity (maintaining symbolic structure in the same modality) and cross-modal translation (transferring meaning across motion and light). Covariance and eigenvalue-decomposition analysis demonstrate that this bio-agentic approach supports clear, expressive, and decentralized communication, with motion-based signaling achieving near-perfect clarity and expressiveness (0.992, 1.000), while LED-only and multi-signal cases showed partial success, maintaining high expressiveness (~1.000) but with much lower clarity (≤0.298). Full article

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

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16 pages, 1842 KB

Open AccessArticle

Effect of Substrate Compliance on the Jumping Mechanism of the Tree Frog (Polypedates dennys)

by Rui Zhou, Baowen Zhang, Zhouyi Wang and Zhendong Dai

Biomimetics 2025, 10(9), 604; https://doi.org/10.3390/biomimetics10090604 - 9 Sep 2025

Animal locomotion in complex environments depends on the ability to adaptively regulate movement in response to substrate mechanics. Tree frogs (Polypedates dennysi), which combine jumping and adhesive capabilities, inhabit arboreal habitats with a wide range of compliant substrates. While previous studies [...] Read more.

Animal locomotion in complex environments depends on the ability to adaptively regulate movement in response to substrate mechanics. Tree frogs (Polypedates dennysi), which combine jumping and adhesive capabilities, inhabit arboreal habitats with a wide range of compliant substrates. While previous studies have offered preliminary insights into their locomotion, the biomechanical mechanisms underlying their adaptability remain poorly characterized. In this study, we developed a stiffness-adjustable takeoff substrate supported by four springs, and combined it with a 3D motion capture system to analyze the jumping dynamics and kinematics of frogs across a broader range of compliant substrates. We found that energy recovery from the substrate was influenced by compliance. On the stiffest substrate, up to 50% of the stored energy was recovered during takeoff, whereas highly compliant substrates caused nonlinear damping, energy dissipation, and even takeoff failure. During takeoff, frogs generated peak normal forces up to 6 times their body weight and fore–aft forces up to 4.5 times their body weight. However, force generation showed limited adaptability to substrate mechanics, while takeoff velocity exhibited stronger adaptability to changes in compliance. These findings reveal a trade-off between substrate mechanics and jump performance. This work provides biomechanical insight into substrate preference and informs the design of bioinspired systems capable of efficient locomotion on compliant substrates. Full article

(This article belongs to the Special Issue Adhesion and Friction in Biological and Bioinspired Systems)

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20 pages, 3941 KB

Open AccessArticle

Self-Supervised Voice Denoising Network for Multi-Scenario Human–Robot Interaction

by Mu Li, Wenjin Xu, Chao Zeng and Ning Wang

Biomimetics 2025, 10(9), 603; https://doi.org/10.3390/biomimetics10090603 - 9 Sep 2025

Human–robot interaction (HRI) via voice command has significantly advanced in recent years, with large Vision–Language–Action (VLA) models demonstrating particular promise in human–robot voice interaction. However, these systems still struggle with environmental noise contamination during voice interaction and lack a specialized denoising network for [...] Read more.

Human–robot interaction (HRI) via voice command has significantly advanced in recent years, with large Vision–Language–Action (VLA) models demonstrating particular promise in human–robot voice interaction. However, these systems still struggle with environmental noise contamination during voice interaction and lack a specialized denoising network for multi-speaker command isolation in an overlapping speech scenario. To overcome these challenges, we introduce a method to enhance voice command-based HRI in noisy environments, leveraging synthetic data and a self-supervised denoising network to enhance its real-world applicability. Our approach focuses on improving self-supervised network performance in denoising mixed-noise audio through training data scaling. Extensive experiments show our method outperforms existing approaches in simulation and achieves 7.5% higher accuracy than the state-of-the-art method in noisy real-world environments, enhancing voice-guided robot control. Full article

(This article belongs to the Special Issue Intelligent Human–Robot Interaction: 4th Edition)

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11 pages, 429 KB

Open AccessReview

Bioinspired Approaches and Their Philosophical–Ethical Dimensions: A Narrative Review

by Louisa Estadieu, Julius Fenn, Michael Gorki, Philipp Höfele and Oliver Müller

Biomimetics 2025, 10(9), 602; https://doi.org/10.3390/biomimetics10090602 - 9 Sep 2025

The environmental crisis demands transformative solutions on both technological and societal levels. Bioinspired approaches, which draw from the principles of natural systems, have emerged as a promising interdisciplinary framework to address these challenges. These approaches not only drive technological innovation but also provoke [...] Read more.

The environmental crisis demands transformative solutions on both technological and societal levels. Bioinspired approaches, which draw from the principles of natural systems, have emerged as a promising interdisciplinary framework to address these challenges. These approaches not only drive technological innovation but also provoke critical philosophical and ethical discourse, particularly in the field of biomimicry. Philosophical and ethical questions include: How can we ethically justify drawing inspiration from nature without exploiting it? How might a shift toward a bioinspired perspective alter our relationship with nature? How could a reorientation toward nature influence ethical frameworks and guide human behavior toward the environment? This narrative review systematically examines key philosophical and ethical perspectives within biomimicry, while focusing on potentials as well as limitations of these approaches to the environmental crisis. In doing so, it explores key perspectives such as “biomimetic ethics”, the “ontology of nature”, “bioinclusivity”, and the “naturalistic fallacy”. Full article

(This article belongs to the Special Issue Biomimetics—A Chance for Sustainable Developments: 2nd Edition)

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16 pages, 4426 KB

Open AccessArticle

Scalable Fabrication of Biomimetic Antibacterial Nanospikes on PMMA Films Using Atmospheric-Pressure Low-Temperature Plasma

by Masashi Yamamoto, Kentaro Tada, Ayumu Takada and Atsushi Sekiguchi

Biomimetics 2025, 10(9), 601; https://doi.org/10.3390/biomimetics10090601 - 8 Sep 2025

Antibacterial surfaces inspired by biological micro- and nanostructures, such as those found on the wings of cicadas and dragonflies, have attracted interest due to their ability to inhibit bacterial adhesion and damage microbial membranes without relying on chemical agents. However, conventional fabrication techniques [...] Read more.

Antibacterial surfaces inspired by biological micro- and nanostructures, such as those found on the wings of cicadas and dragonflies, have attracted interest due to their ability to inhibit bacterial adhesion and damage microbial membranes without relying on chemical agents. However, conventional fabrication techniques like photolithography or nanoimprinting are limited by substrate shape, size, and high operational costs. In this study, we developed a scalable method using atmospheric-pressure low-temperature plasma (APLTP) to fabricate sharp-edged nanospikes on solvent-cast polymethyl methacrylate (PMMA) films. The nanospikes were formed through plasma-induced modification of pores in the film, followed by annealing to control surface wettability while maintaining structural sharpness. Atomic force microscopy confirmed the formation of micro/nanostructures, and contact angle measurements revealed reversible hydrophilicity. Antibacterial performance was evaluated against Escherichia coli using ISO 22196 standards. While the film with only plasma treatment reduced bacterial colonies by 30%, the film annealed after plasma treatment achieved an antibacterial activity value greater than 5, with bacterial counts below the detection limit (<10 CFU). These findings demonstrate that APLTP offers a practical route for large-area fabrication of biomimetic antibacterial coatings on flexible polymer substrates, holding promise for future applications in healthcare, packaging, and public hygiene. Full article

(This article belongs to the Section Biomimetic Surfaces and Interfaces)

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17 pages, 3935 KB

Open AccessArticle

Markerless Force Estimation via SuperPoint-SIFT Fusion and Finite Element Analysis: A Sensorless Solution for Deformable Object Manipulation

by Qingqing Xu, Ruoyang Lai and Junqing Yin

Biomimetics 2025, 10(9), 600; https://doi.org/10.3390/biomimetics10090600 - 8 Sep 2025

Contact-force perception is a critical component of safe robotic grasping. With the rapid advances in embodied intelligence technology, humanoid robots have enhanced their multimodal perception capabilities. Conventional force sensors face limitations, such as complex spatial arrangements, installation challenges at multiple nodes, and potential [...] Read more.

Contact-force perception is a critical component of safe robotic grasping. With the rapid advances in embodied intelligence technology, humanoid robots have enhanced their multimodal perception capabilities. Conventional force sensors face limitations, such as complex spatial arrangements, installation challenges at multiple nodes, and potential interference with robotic flexibility. Consequently, these conventional sensors are unsuitable for biomimetic robot requirements in object perception, natural interaction, and agile movement. Therefore, this study proposes a sensorless external force detection method that integrates SuperPoint-Scale Invariant Feature Transform (SIFT) feature extraction with finite element analysis to address force perception challenges. A visual analysis method based on the SuperPoint-SIFT feature fusion algorithm was implemented to reconstruct a three-dimensional displacement field of the target object. Subsequently, the displacement field was mapped to the contact force distribution using finite element modeling. Experimental results demonstrate a mean force estimation error of 7.60% (isotropic) and 8.15% (anisotropic), with RMSE < 8%, validated by flexible pressure sensors. To enhance the model’s reliability, a dual-channel video comparison framework was developed. By analyzing the consistency of the deformation patterns and mechanical responses between the actual compression and finite element simulation video keyframes, the proposed approach provides a novel solution for real-time force perception in robotic interactions. The proposed solution is suitable for applications such as precision assembly and medical robotics, where sensorless force feedback is crucial. Full article

(This article belongs to the Special Issue Bio-Inspired Intelligent Robot)

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11 pages, 2878 KB

Open AccessArticle

Bioinspired Polyvinyl Alcohol-Based Foam Fabricated via Supercritical Carbon Dioxide Foaming for Atmospheric Water Harvesting

by Yingying Chen, Changjun Guo, Hao Wang, Jiabao Lu, Heng Xie and Ting Wu

Biomimetics 2025, 10(9), 599; https://doi.org/10.3390/biomimetics10090599 - 8 Sep 2025

The intensifying freshwater crisis underscores the critical need for all-weather, low-energy atmospheric water harvesting technologies. Inspired by the scale-like protrusions and interconnected channels of Tillandsia leaves that enable efficient water capture and release, a polyvinyl alcohol-based foam featuring a three-dimensional porous structure is [...] Read more.

The intensifying freshwater crisis underscores the critical need for all-weather, low-energy atmospheric water harvesting technologies. Inspired by the scale-like protrusions and interconnected channels of Tillandsia leaves that enable efficient water capture and release, a polyvinyl alcohol-based foam featuring a three-dimensional porous structure is fabricated using the supercritical carbon dioxide foaming technology. Compared to the traditional freeze-drying method, this approach significantly reduces preparation energy consumption and shortens the production cycle. Lithium chloride integration endows the foam with exceptional moisture absorption capacity, reaching 300% of its weight. Leveraging graphene’s outstanding photothermal conversion properties, the foam achieves a photothermal dehydration rate of 80.7% within 80 min under 1 Sun irradiation, demonstrating a rapid water release capacity. Furthermore, the polyvinyl alcohol-based foam exhibits no performance degradation after 60 cycles, indicating remarkable stability. This technology provides a scalable, low-cost, and all-climate-applicable solution for water-scarce regions. Full article

(This article belongs to the Special Issue Design and Fabrication of Biomimetic Smart Materials)

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12 pages, 5729 KB

Open AccessCommunication

Biomimetic Dual-Sensing Bone Scaffolds: Characterization and In Vitro Evaluation Under Dynamic Culturing Conditions

by Damion T. Dixon, Erika N. Landree and Cheryl T. Gomillion

Biomimetics 2025, 10(9), 598; https://doi.org/10.3390/biomimetics10090598 - 8 Sep 2025

The regeneration of large segmental bone defects remains a significant challenge. While electrical stimulation has demonstrated the potential to accelerate bone healing, clinical translation has been hindered by the lack of safe, localized delivery methods. In this study, we present a novel strategy [...] Read more.

The regeneration of large segmental bone defects remains a significant challenge. While electrical stimulation has demonstrated the potential to accelerate bone healing, clinical translation has been hindered by the lack of safe, localized delivery methods. In this study, we present a novel strategy combining piezoelectric and electrically conductive polymers with allograft demineralized bones to create stimuli-responsive, biologically relevant scaffolds via pneumatic 3D printing. These scaffolds exhibit enhanced piezoelectric potential and tunable electrical properties, enabling both electrical and mechanical stimulation of cells (without external stimulators). Under dynamic culturing conditions (i.e., ultrasound stimulation), human bone marrow-derived mesenchymal stromal cells cultured on these scaffolds displayed significantly elevated osteogenic protein expression (i.e., alkaline phosphatase and osteocalcin) and mineralization (confirmed via xylenol orange mineral staining) after two weeks. This work introduces a bioinspired, printable ink in conjunction with a simple fabrication approach for creating dual-responsive scaffolds with high potential for functional bone tissue regeneration. Full article

(This article belongs to the Special Issue Biomimetic Materials for Bone Tissue Engineering)

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11 pages, 2963 KB

Open AccessCommunication

Optimization Design of Haptic Units for Perception Feedback Interfaces Based on Vibrotactile Amplitude Modulation

by Weichao Guo, Jingchen Huang, Lechuan Zhou, Yun Fang, Li Jiang and Xinjun Sheng

Biomimetics 2025, 10(9), 597; https://doi.org/10.3390/biomimetics10090597 - 7 Sep 2025

Tactile sensation is a crucial sensory pathway for humans to acquire information from the environment, and vibration feedback is one form of tactile feedback, offering advantages such as low cost, ease of integration, and high comfort. Avoiding mechanical crosstalk without changing the spacing [...] Read more.

Tactile sensation is a crucial sensory pathway for humans to acquire information from the environment, and vibration feedback is one form of tactile feedback, offering advantages such as low cost, ease of integration, and high comfort. Avoiding mechanical crosstalk without changing the spacing between vibration units is a significant challenge in the design of haptic interfaces. This work focuses on the joint optimization design of vibration source characteristics and packaging materials of vibration units. From a theoretical modeling perspective, we explore the correlation between material properties and the amplitude of vibrations generated on the skin surface. A three-layer vibration unit optimization design scheme using a pogo pin structure is thus proposed. Parameters are optimized through finite element analysis, and experimental results prove that the three-layer vibration unit with pogo pins has amplitude modulation capabilities, laying the foundation for the design of array-based vibration tactile feedback interfaces and human-inspired grasp control. Full article

(This article belongs to the Special Issue Human-Inspired Grasp Control in Robotics 2025)

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