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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, 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 20.3 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the first half of 2024).
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: 3.4 (2023); 5-Year Impact Factor: 3.8 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2313-7673

Latest Articles

24 pages, 6036 KiB

Open AccessArticle

Design and Optimization of a Custom-Made Six-Bar Exoskeleton for Pulp Pinch Grasp Rehabilitation in Stroke Patients

by Javier Andrés-Esperanza, José L. Iserte-Vilar and Víctor Roda-Casanova

Biomimetics 2024, 9(10), 616; https://doi.org/10.3390/biomimetics9100616 (registering DOI) - 11 Oct 2024

Stroke often causes neuromotor disabilities, impacting index finger function in daily activities. Due to the role of repetitive, even passive, finger movements in neuromuscular re-education and spasticity control, this study aims to design a rehabilitation exoskeleton based on the pulp pinch movement. The [...] Read more.

Stroke often causes neuromotor disabilities, impacting index finger function in daily activities. Due to the role of repetitive, even passive, finger movements in neuromuscular re-education and spasticity control, this study aims to design a rehabilitation exoskeleton based on the pulp pinch movement. The exoskeleton uses an underactuated RML topology with a single degree of mobility, customized from 3D scans of the patient’s hand. It consists of eight links, incorporating two consecutive four-bar mechanisms and the third inversion of a crank–slider. A two-stage genetic optimization was applied, first to the location of the intermediate joint between the two four-bar mechanisms and later to the remaining dimensions. A targeted genetic optimization process monitored two quality metrics: average mechanical advantage from extension to flexion, and its variability. By analyzing the relationship between these metrics and key parameters at different synthesis stages, the population evaluated is reduced by up to 96.2%, compared to previous studies for the same problem. This custom-fit exoskeleton uses a small linear actuator to deliver a stable 12.45 N force to the fingertip with near-constant mechanical advantage during flexion. It enables repetitive pulp pinch movements in a flaccid finger, improving rehabilitation consistency and facilitating home-based therapy. Full article

(This article belongs to the Special Issue Bionic Technology—Robotic Exoskeletons and Prostheses: 2nd Edition)

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17 pages, 3304 KiB

Open AccessArticle

MTC-NET: A Multi-Channel Independent Anomaly Detection Method for Network Traffic

by Xiaoyong Zhao, Chengjin Huang and Lei Wang

Biomimetics 2024, 9(10), 615; https://doi.org/10.3390/biomimetics9100615 - 10 Oct 2024

In recent years, deep learning-based approaches, particularly those leveraging the Transformer architecture, have garnered widespread attention for network traffic anomaly detection. However, when dealing with noisy data sets, directly inputting network traffic sequences into Transformer networks often significantly degrades detection performance due to [...] Read more.

In recent years, deep learning-based approaches, particularly those leveraging the Transformer architecture, have garnered widespread attention for network traffic anomaly detection. However, when dealing with noisy data sets, directly inputting network traffic sequences into Transformer networks often significantly degrades detection performance due to interference and noise across dimensions. In this paper, we propose a novel multi-channel network traffic anomaly detection model, MTC-Net, which reduces computational complexity and enhances the model’s ability to capture long-distance dependencies. This is achieved by decomposing network traffic sequences into multiple unidimensional time sequences and introducing a patch-based strategy that enables each sub-sequence to retain local semantic information. A backbone network combining Transformer and CNN is employed to capture complex patterns, with information from all channels being fused at the final classification header in order to achieve modelling and detection of complex network traffic patterns. The experimental results demonstrate that MTC-Net outperforms existing state-of-the-art methods in several evaluation metrics, including accuracy, precision, recall, and F1 score, on four publicly available data sets: KDD Cup 99, NSL-KDD, UNSW-NB15, and CIC-IDS2017. Full article

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

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5 pages, 169 KiB

Open AccessEditorial

Editorial Board Members’ Collection Series: Biomimetic Design, Constructions and Devices in Times of Change I

by Ille C. Gebeshuber

Biomimetics 2024, 9(10), 614; https://doi.org/10.3390/biomimetics9100614 - 10 Oct 2024

In light of recent global crises, including climate change, species extinction, the COVID-19 pandemic, social upheavals and energy supply challenges, this Special Issue of Biomimetics, entitled “Editorial Board Members’ Collection Series: Biomimetic Design, Constructions and Devices in Times of Change”, aims to [...] Read more.

In light of recent global crises, including climate change, species extinction, the COVID-19 pandemic, social upheavals and energy supply challenges, this Special Issue of Biomimetics, entitled “Editorial Board Members’ Collection Series: Biomimetic Design, Constructions and Devices in Times of Change”, aims to explore innovative solutions through biomimetics. This collection features research on various biomimetic applications, such as the peptide-based detection of SARS-CoV-2 antibodies, ergonomic improvements for prolonged sitting, biomimicry industry trends, prosthetic foot functionality and agricultural machinery efficiency. The methods employed include peptide synthesis for diagnostics, simulation software for ergonomic designs, patent analysis for biomimicry trends and engineering discrete element methods for agricultural applications. The findings highlight significant advancements in health diagnostics, ergonomic safety, technological development, prosthetics and sustainable agriculture. The research underscores the potential of biomimetic approaches to address contemporary challenges by leveraging nature-inspired designs and processes. These insights contribute to a broader understanding of how biomimetic principles can lead to adaptive and sustainable solutions in times of change, promoting resilience and innovation across various fields. Full article

(This article belongs to the Special Issue Editorial Board Members' Collection Series: Biomimetic Design, Constructions and Devices in Times of Change)

13 pages, 979 KiB

Open AccessArticle

A Multimodal Multi-Objective Feature Selection Method for Intelligent Rating Models of Unmanned Highway Toll Stations

by Zhaohui Gao, Huan Mo, Zicheng Yan and Qinqin Fan

Biomimetics 2024, 9(10), 613; https://doi.org/10.3390/biomimetics9100613 - 10 Oct 2024

To facilitate the intelligent classification of unmanned highway toll stations, selecting effective and useful features is pivotal. This process involves achieving a tradeoff between the number of features and the classification accuracy while also reducing the acquisition costs of features. To address these [...] Read more.

To facilitate the intelligent classification of unmanned highway toll stations, selecting effective and useful features is pivotal. This process involves achieving a tradeoff between the number of features and the classification accuracy while also reducing the acquisition costs of features. To address these challenges, a multimodal multi-objective feature selection (MMOFS) method is proposed in the current study. In the MMOFS, we utilize a multimodal multi-objective evolutionary algorithm to choose features for the unmanned highway toll station classification model and use the random forest method for classification. The primary contribution of the current study is to propose a feature selection method specifically designed for the classification model of unmanned highway toll stations. Experimental results using actual data from highway toll stations demonstrate that the proposed MMOFS outperforms the other two competitors in terms of PSP, HV, and IGD. Furthermore, the proposed algorithm can provide decision-makers with multiple equivalent feature selection schemes. This approach achieves a harmonious balance between the model complexity and the classification accuracy based on actual scenarios, thereby providing guidance for the construction of unmanned highway toll stations. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)

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17 pages, 1623 KiB

Open AccessArticle

Autonomous Robot Task Execution in Flexible Manufacturing: Integrating PDDL and Behavior Trees in ARIAC 2023

by Ruikai Liu, Guangxi Wan, Maowei Jiang, Haojie Chen and Peng Zeng

Biomimetics 2024, 9(10), 612; https://doi.org/10.3390/biomimetics9100612 - 10 Oct 2024

The Agile Robotics for Industrial Automation Competition (ARIAC) was established to advance flexible manufacturing, aiming to increase the agility of robotic assembly systems in unstructured and dynamic industrial environments. ARIAC 2023 introduced eight agility challenges involving faulty parts, flipped parts, faulty grippers, robot [...] Read more.

The Agile Robotics for Industrial Automation Competition (ARIAC) was established to advance flexible manufacturing, aiming to increase the agility of robotic assembly systems in unstructured and dynamic industrial environments. ARIAC 2023 introduced eight agility challenges involving faulty parts, flipped parts, faulty grippers, robot malfunctions, sensor blackouts, high-priority orders, insufficient parts, and human safety. Given the unpredictability of these scenarios, it is impractical to develop a specific strategy for each possible situation. To address these issues, this paper presents a hierarchical framework for autonomous robotic task generation and execution in dynamic scenarios. The framework is divided into a task level and an execution level. Initially, an immediate task management strategy is adopted at the task level, which reasonably decomposes dynamic tasks and allocates short-term tasks to the floor robot and ceiling robot. Later, at the execution level, each robot is designed with an agent architecture that combines PDDL planning with the quick response of behavior trees. Finally, the effectiveness and practicality of the proposed framework were thoroughly validated in ARIAC 2023. Full article

(This article belongs to the Special Issue Artificial Intelligence for Autonomous Robots: 3rd Edition)

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15 pages, 6180 KiB

Open AccessArticle

Bionic Optimization Design and Fatigue Life Prediction of a Honeycomb-Structured Wheel Hub

by Na Liu, Xujie Liu, Yueming Jiang, Peng Liu, Yuanyuan Gao, Hang Ding and Yujun Zhao

Biomimetics 2024, 9(10), 611; https://doi.org/10.3390/biomimetics9100611 - 9 Oct 2024

The wheel hub is an important component of the wheel, and a good hub design can significantly improve vehicle handling, stability, and braking performance, ensuring safe driving. This article optimized the hub structure through morphological aspects, where reducing the hub weight contributed to [...] Read more.

The wheel hub is an important component of the wheel, and a good hub design can significantly improve vehicle handling, stability, and braking performance, ensuring safe driving. This article optimized the hub structure through morphological aspects, where reducing the hub weight contributed to enhanced fuel efficiency and overall vehicle performance. By referencing honeycombed structures, a bionic hub design is numerically simulated using finite element analysis and response surface optimization. The results showed that under the optimization of the response surface analytical model, the maximum stress of the optimized bionic hub was 109.34 MPa, compared to 119.77 MPa for the standard hub, representing an 8.7% reduction in maximum stress. The standard hub weighs 34.02 kg, while the optimized hub weight was reduced to 29.89 kg, a decrease of 12.13%. A fatigue analysis on the optimized hub indicated that at a stress of 109.34 MPa, the minimum load cycles were 4.217 × 10⁵ at the connection point with the half-shaft, meeting the fatigue life requirements for commercial vehicle hubs outlined in the national standard GB/T 5334-2021. Full article

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17 pages, 2983 KiB

Open AccessArticle

Pose Estimation of a Cobot Implemented on a Small AI-Powered Computing System and a Stereo Camera for Precision Evaluation

by Marco-Antonio Cabrera-Rufino, Juan-Manuel Ramos-Arreguín, Marco-Antonio Aceves-Fernandez, Efren Gorrostieta-Hurtado, Jesus-Carlos Pedraza-Ortega and Juvenal Rodríguez-Resendiz

Biomimetics 2024, 9(10), 610; https://doi.org/10.3390/biomimetics9100610 - 9 Oct 2024

The precision of robotic manipulators in the industrial or medical field is very important, especially when it comes to repetitive or exhaustive tasks. Geometric deformations are the most common in this field. For this reason, new robotic vision techniques have been proposed, including [...] Read more.

The precision of robotic manipulators in the industrial or medical field is very important, especially when it comes to repetitive or exhaustive tasks. Geometric deformations are the most common in this field. For this reason, new robotic vision techniques have been proposed, including 3D methods that made it possible to determine the geometric distances between the parts of a robotic manipulator. The aim of this work is to measure the angular position of a robotic arm with six degrees of freedom. For this purpose, a stereo camera and a convolutional neural network algorithm are used to reduce the degradation of precision caused by geometric errors. This method is not intended to replace encoders, but to enhance accuracy by compensating for degradation through an intelligent visual measurement system. The camera is tested and the accuracy is about one millimeter. The implementation of this method leads to better results than traditional and simple neural network methods. Full article

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23 pages, 7449 KiB

Open AccessArticle

Fully Interpretable Deep Learning Model Using IR Thermal Images for Possible Breast Cancer Cases

by Yerken Mirasbekov, Nurduman Aidossov, Aigerim Mashekova, Vasilios Zarikas, Yong Zhao, Eddie Yin Kwee Ng and Anna Midlenko

Biomimetics 2024, 9(10), 609; https://doi.org/10.3390/biomimetics9100609 - 9 Oct 2024

Breast cancer remains a global health problem requiring effective diagnostic methods for early detection, in order to achieve the World Health Organization’s ultimate goal of breast self-examination. A literature review indicates the urgency of improving diagnostic methods and identifies thermography as a promising, [...] Read more.

Breast cancer remains a global health problem requiring effective diagnostic methods for early detection, in order to achieve the World Health Organization’s ultimate goal of breast self-examination. A literature review indicates the urgency of improving diagnostic methods and identifies thermography as a promising, cost-effective, non-invasive, adjunctive, and complementary detection method. This research explores the potential of using machine learning techniques, specifically Bayesian networks combined with convolutional neural networks, to improve possible breast cancer diagnosis at early stages. Explainable artificial intelligence aims to clarify the reasoning behind any output of artificial neural network-based models. The proposed integration adds interpretability of the diagnosis, which is particularly significant for a medical diagnosis. We constructed two diagnostic expert models: Model A and Model B. In this research, Model A, combining thermal images after the explainable artificial intelligence process together with medical records, achieved an accuracy of 84.07%, while model B, which also includes a convolutional neural network prediction, achieved an accuracy of 90.93%. These results demonstrate the potential of explainable artificial intelligence to improve possible breast cancer diagnosis, with very high accuracy. Full article

(This article belongs to the Special Issue New Biomimetic Advances in Signal and Image Processing for Biomedical Applications)

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15 pages, 6834 KiB

Open AccessArticle

Investigation of 9 True Weevil (Curculionidae Latreille, 1802) Species for Chitin Extraction

by Zhenying Mei, Luc Vincent, Caroline R. Szczepanski, René-Paul Godeau, Pavel Kuzhir and Guilhem Godeau

Biomimetics 2024, 9(10), 608; https://doi.org/10.3390/biomimetics9100608 - 8 Oct 2024

Chitin, the second most abundant biopolymer after cellulose, is an important resource for biosourced materials. The global demand for chitin is rapidly increasing, however, the majority of industrial chitin is sourced from crustacean shells, which may be less accessible in regions without seafood [...] Read more.

Chitin, the second most abundant biopolymer after cellulose, is an important resource for biosourced materials. The global demand for chitin is rapidly increasing, however, the majority of industrial chitin is sourced from crustacean shells, which may be less accessible in regions without seafood waste. Therefore, it is crucial to explore alternative chitin sources, such as those derived from beetles and other arthropods. This study investigated chitin extraction from nine species of Curculionidae (true weevils), which are recognized as crop pests. The extraction process and yields were described, and the isolated chitin was characterized by SEM, IR spectroscopy, elemental analysis, XRD, and ash and water content measurements. This work highlights the potential of Curculionidae as an alternative chitin source. Full article

(This article belongs to the Special Issue Chitin and Chitosan Materials for Tomorrow)

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26 pages, 6476 KiB

Open AccessArticle

YOLO-LFPD: A Lightweight Method for Strip Surface Defect Detection

by Jianbo Lu, Mingrui Zhu, Kaixian Qin and Xiaoya Ma

Biomimetics 2024, 9(10), 607; https://doi.org/10.3390/biomimetics9100607 - 8 Oct 2024

Strip steel surface defect recognition research has important research significance in industrial production. Aiming at the problems of defect feature extraction, slow detection speed, and insufficient datasets, YOLOv5 is improved on the basis of YOLOv5, and the YOLO-LFPD (lightweight fine particle detection) model [...] Read more.

Strip steel surface defect recognition research has important research significance in industrial production. Aiming at the problems of defect feature extraction, slow detection speed, and insufficient datasets, YOLOv5 is improved on the basis of YOLOv5, and the YOLO-LFPD (lightweight fine particle detection) model is proposed. By introducing the RepVGG (Re-param VGG) module, the robustness of the model is enhanced, and the expressive ability of the model is improved. FasterNet is used to replace the backbone network, which ensures accuracy and accelerates the inference speed, making the model more suitable for real-time monitoring. The use of pruning, a GA genetic algorithm with OTA loss function, further reduces the model size while better learning the strip steel defect feature information, thus improving the generalisation ability and accuracy of the model. The experimental results show that the introduction of the RepVGG module and the use of FasterNet can well improve the model performance, with a reduction of 48% in the number of parameters, a reduction of 13% in the number of GFLOPs, an inference time of 77% of the original, and an optimal accuracy compared with the network models in recent years. The experimental results on the NEU-DET dataset show that the accuracy of YOLO-LFPD is improved by 3% to 81.2%, which is better than other models, and provides new ideas and references for the lightweight strip steel surface defect detection scenarios and application deployment. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)

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12 pages, 1792 KiB

Open AccessArticle

3D Printing Materials Mimicking Human Tissues after Uptake of Iodinated Contrast Agents for Anthropomorphic Radiology Phantoms

by Peter Homolka, Lara Breyer and Friedrich Semturs

Biomimetics 2024, 9(10), 606; https://doi.org/10.3390/biomimetics9100606 - 8 Oct 2024

(1) Background: 3D printable materials with accurately defined iodine content enable the development and production of radiological phantoms that simulate human tissues, including lesions after contrast administration in medical imaging with X-rays. These phantoms provide accurate, stable and reproducible models with defined iodine [...] Read more.

(1) Background: 3D printable materials with accurately defined iodine content enable the development and production of radiological phantoms that simulate human tissues, including lesions after contrast administration in medical imaging with X-rays. These phantoms provide accurate, stable and reproducible models with defined iodine concentrations, and 3D printing allows maximum flexibility and minimal development and production time, allowing the simulation of anatomically correct anthropomorphic replication of lesions and the production of calibration and QA standards in a typical medical research facility. (2) Methods: Standard printing resins were doped with an iodine contrast agent and printed using a consumer 3D printer, both (resins and printer) available from major online marketplaces, to produce printed specimens with iodine contents ranging from 0 to 3.0% by weight, equivalent to 0 to 3.85% elemental iodine per volume, covering the typical levels found in patients. The printed samples were scanned in a micro-CT scanner to measure the properties of the materials in the range of the iodine concentrations used. (3) Results: Both mass density and attenuation show a linear dependence on iodine concentration (R² = 1.00), allowing highly accurate, stable, and predictable results. (4) Conclusions: Standard 3D printing resins can be doped with liquids, avoiding the problem of sedimentation, resulting in perfectly homogeneous prints with accurate dopant content. Iodine contrast agents are perfectly suited to dope resins with appropriate iodine concentrations to radiologically mimic tissues after iodine uptake. In combination with computer-aided design, this can be used to produce printed objects with precisely defined iodine concentrations in the range of up to a few percent of elemental iodine, with high precision and anthropomorphic shapes. Applications include radiographic phantoms for detectability studies and calibration standards in projective X-ray imaging modalities, such as contrast-enhanced dual energy mammography (abbreviated CEDEM, CEDM, TICEM, or CESM depending on the equipment manufacturer), and 3-dimensional modalities like CT, including spectral and dual energy CT (DECT), and breast tomosynthesis. Full article

(This article belongs to the Special Issue Bio-Inspired Additive Manufacturing Materials and Structures)

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12 pages, 7500 KiB

Open AccessArticle

Bionic Design of High-Performance Joints: Differences in Failure Mechanisms Caused by the Different Structures of Beetle Femur–Tibial Joints

by Jiandong Cui, Yubo Wang, Sen Lin, Zhiwei Tuo, Zhaohua Lin, Yunhong Liang and Luquan Ren

Biomimetics 2024, 9(10), 605; https://doi.org/10.3390/biomimetics9100605 - 8 Oct 2024

Beetle femur–tibial joints can bear large loads, and the joint structure plays a crucial role. Differences in living habits will lead to differences in femur–tibial joint structure, resulting in different mechanical properties. Here, we determined the structural characteristics of the femur–tibial joints of [...] Read more.

Beetle femur–tibial joints can bear large loads, and the joint structure plays a crucial role. Differences in living habits will lead to differences in femur–tibial joint structure, resulting in different mechanical properties. Here, we determined the structural characteristics of the femur–tibial joints of three species of beetles with different living habits. The tibia of Scarabaeidae Protaetia brevitarsis and Cetoniidae Torynorrhina fulvopilosa slide through cashew-shaped bumps on both sides of the femur in a guide rail consisting of a ring and a cone bump. The femur–tibial joint of Buprestidae Chrysodema radians is composed of a conical convex tibia and a circular concave femur. A bionic structure design was developed out based on the characteristics of the structure of the femur–tibial joints. Differences in the failure of different joint models were obtained through experiments and finite element analysis. The experimental results show that although the spherical connection model can bear low loads, it can maintain partial integrity of the structure and avoid complete failure. The cuboid connection model shows a higher load-bearing capacity, but its failure mode is irreversible deformation. As key parts of rotatable mechanisms, the bionic models have the potential for wide application in the high-load engineering field. Full article

(This article belongs to the Special Issue Biomimicry and Functional Materials: 4th Edition)

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15 pages, 1280 KiB

Open AccessArticle

Adaptive Bi-Operator Evolution for Multitasking Optimization Problems

by Changlong Wang, Zijia Wang and Zheng Kou

Biomimetics 2024, 9(10), 604; https://doi.org/10.3390/biomimetics9100604 - 8 Oct 2024

The field of evolutionary multitasking optimization (EMTO) has been a highly anticipated research topic in recent years. EMTO aims to utilize evolutionary algorithms to concurrently solve complex problems involving multiple tasks. Despite considerable advancements in this field, numerous evolutionary multitasking algorithms continue to [...] Read more.

The field of evolutionary multitasking optimization (EMTO) has been a highly anticipated research topic in recent years. EMTO aims to utilize evolutionary algorithms to concurrently solve complex problems involving multiple tasks. Despite considerable advancements in this field, numerous evolutionary multitasking algorithms continue to use a single evolutionary search operator (ESO) throughout the evolution process. This strategy struggles to completely adapt to different tasks, consequently hindering the algorithm’s performance. To overcome this challenge, this paper proposes multitasking evolutionary algorithms via an adaptive bi-operator strategy (BOMTEA). BOMTEA adopts a bi-operator strategy and adaptively controls the selection probability of each ESO according to its performance, which can determine the most suitable ESO for various tasks. In an experiment, BOMTEA showed outstanding results on two well-known multitasking benchmark tests, CEC17 and CEC22, and significantly outperformed other comparative algorithms. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)

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45 pages, 16184 KiB

Open AccessArticle

MSAO-EDA: A Modified Snow Ablation Optimizer by Hybridizing with Estimation of Distribution Algorithm

by Wuke Li, Xiaoxiao Chen and Hector Chimeremeze Okere

Biomimetics 2024, 9(10), 603; https://doi.org/10.3390/biomimetics9100603 - 7 Oct 2024

Metaheuristic algorithms provide reliable and effective methods for solving challenging optimization problems. The snow ablation algorithm (SAO) performs favorably as a physics-based metaheuristic algorithm. Nevertheless, SAO has some shortcomings. SAO is overpowered in its exploitation, has difficulty in balancing the proportion of global [...] Read more.

Metaheuristic algorithms provide reliable and effective methods for solving challenging optimization problems. The snow ablation algorithm (SAO) performs favorably as a physics-based metaheuristic algorithm. Nevertheless, SAO has some shortcomings. SAO is overpowered in its exploitation, has difficulty in balancing the proportion of global and local search, and is prone to encountering local optimum traps when confronted with complex problems. To improve the capability of SAO, this paper proposes a modified snow ablation algorithm hybrid distribution estimation algorithm named MSAO-EDA. In this work, a collaborative search framework is proposed where SAO and EDA can be organically integrated together to fully utilize the exploitation capability of SAO and the exploration capability of EDA. Secondly, an offset EDA approach that combines the optimal solution and the agent itself is used to replace SAO’s exploration strategy for the purpose of enhancing SAO’s exploration capability. Finally, the convergence of SAO is accelerated by selecting the next generation of agents through a greedy strategy. MSAO-EDA is tested on the CEC 2017 and CEC 2022 test suites and compared with EO, RIME, MRFO, CFOA, and four advanced algorithms, AFDBARO, CSOAOA, EOSMA, and JADE. The experimental results show that MSAO-EDA has excellent efficiency in numerical optimization problems and is a highly competitive SAO variant. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)

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35 pages, 3615 KiB

Open AccessArticle

A Hybrid Nonlinear Whale Optimization Algorithm with Sine Cosine for Global Optimization

by Yubao Xu and Jinzhong Zhang

Biomimetics 2024, 9(10), 602; https://doi.org/10.3390/biomimetics9100602 - 7 Oct 2024

The whale optimization algorithm (WOA) is constructed on a whale’s bubble-net scavenging pattern and emulates encompassing prey, bubble-net devouring prey, and stochastic capturing for prey to establish the global optimal values. Nevertheless, the WOA has multiple deficiencies, such as restricted precision, sluggish convergence [...] Read more.

The whale optimization algorithm (WOA) is constructed on a whale’s bubble-net scavenging pattern and emulates encompassing prey, bubble-net devouring prey, and stochastic capturing for prey to establish the global optimal values. Nevertheless, the WOA has multiple deficiencies, such as restricted precision, sluggish convergence acceleration, insufficient population variety, easy premature convergence, and restricted operational efficiency. The sine cosine algorithm (SCA) constructed on the oscillation attributes of the cosine and sine coefficients in mathematics is a stochastic optimization methodology. The SCA upgrades population variety, amplifies the search region, and accelerates international investigation and regional extraction. Therefore, a hybrid nonlinear WOA with SCA (SCWOA) is emphasized to estimate benchmark functions and engineering designs, and the ultimate intention is to investigate reasonable solutions. Compared with other algorithms, such as BA, CapSA, MFO, MVO, SAO, MDWA, and WOA, SCWOA exemplifies a superior convergence effectiveness and greater computation profitability. The experimental results emphasize that the SCWOA not only integrates investigation and extraction to avoid premature convergence and realize the most appropriate solution but also exhibits superiority and practicability to locate greater computation precision and faster convergence speed. Full article

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13 pages, 1828 KiB

Open AccessArticle

Gender Differences in Performing an Overhead Drilling Task Using an Exoskeleton—A Cross-Sectional Study

by Bettina Wollesen, Julia Gräf, Sander De Bock, Eligia Alfio, María Alejandra Díaz and Kevin De Pauw

Biomimetics 2024, 9(10), 601; https://doi.org/10.3390/biomimetics9100601 - 7 Oct 2024

(1) Exoskeletons offer potential benefits for overhead working tasks, but gender effects or differences are unclear. This study aimed to compare the performance as well as subjective body strain and comfort of men and women using an upper-body exoskeleton. (2) n = 20 [...] Read more.

(1) Exoskeletons offer potential benefits for overhead working tasks, but gender effects or differences are unclear. This study aimed to compare the performance as well as subjective body strain and comfort of men and women using an upper-body exoskeleton. (2) n = 20 female and n = 16 male participants performed an overhead drilling task with and without a passive upper-body exoskeleton in a randomized cross-over study. The task performance of different movement phases, perceived exertion, and ease of use were measured to compare gender differences. One- and two-way analyses were used to compare genders in the different conditions. The body mass index (BMI) was included as a covariate. (3) Gender differences in task performance were found for error integrals (p < 0.001) with higher values in male participants. Moreover, there was a significant interaction effect for gender x exoskeleton use. While females showed performance decrements in aiming with exoskeleton use, the males’ performance increased (p = 0.025). No other gender differences were observed. (4) Gender differences in task performance using an upper-body industrial exoskeleton were less detectable than expected, indicating that body composition and anthropometrics might be valuable indicators for performance including assisting devices. Moreover, future studies should also integrate the examination of muscle activity to gain more insights into potential gender movement control patterns. Full article

(This article belongs to the Special Issue Bionic Technology—Robotic Exoskeletons and Prostheses: 2nd Edition)

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23 pages, 72307 KiB

Open AccessReview

Biomimetic Origami: A Biological Influence in Design

by Hadi Ebrahimi Fakhari, Juan Rosario Barboza and Pezhman Mardanpour

Biomimetics 2024, 9(10), 600; https://doi.org/10.3390/biomimetics9100600 - 4 Oct 2024

Origami, the art of paper folding, has long fascinated researchers and designers in its potential to replicate and tap the complexity of nature. In this paper, we pursue the crossing of origami engineering structures and biology, the realm of biologically-inspired origami structures categorized [...] Read more.

Origami, the art of paper folding, has long fascinated researchers and designers in its potential to replicate and tap the complexity of nature. In this paper, we pursue the crossing of origami engineering structures and biology, the realm of biologically-inspired origami structures categorized by the two biggest taxonomy kingdoms and DNA origami. Given the diversity of life forms that Earth comprises, we pursue an analysis of biomimetic designs that resemble intricate patterns and functionalities occurring in nature. Our research begins by setting out a taxonomic framework for the classification of origami structures based on biologically important kingdoms. From each of these, we explore the engineering structures inspired by morphological features, behaviors, and ecological adaptations of organisms. We also discuss implications in realms such as sustainability, biomaterials development, and bioinspired robotics. Thus, by parlaying the principles found in nature’s design playbook through the art of folding, biologically inspired origami becomes fertile ground for interdisciplinary collaboration and creativity. Through this approach, we aim to inspire readers, researchers, and designers to embark on a journey of discovery in which the boundaries between art, science, and nature are blurred, providing a foundation for innovation to thrive. Full article

(This article belongs to the Special Issue Bio-Inspired Mechanical Design and Control)

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13 pages, 1007 KiB

Open AccessArticle

A Fast Grasp Planning Algorithm for Humanoid Robot Hands

by Ziqi Liu, Li Jiang and Ming Cheng

Biomimetics 2024, 9(10), 599; https://doi.org/10.3390/biomimetics9100599 - 4 Oct 2024

Grasp planning is crucial for robots to perform precision grasping tasks, where determining the grasp points significantly impacts the performance of the robotic hand. Currently, the majority of grasp planning methods based on analytic approaches solve the problem by transforming it into a [...] Read more.

Grasp planning is crucial for robots to perform precision grasping tasks, where determining the grasp points significantly impacts the performance of the robotic hand. Currently, the majority of grasp planning methods based on analytic approaches solve the problem by transforming it into a nonlinear constrained planning problem. This method often requires performing convex hull computations, which tend to have high computational complexity. This paper proposes a new algorithm for calculating multi-finger force-closure grasps of three-dimensional objects based on humanoid multi-fingered hands. Firstly, sufficient conditions for the multi-finger force-closure grasps of three-dimensional objects are derived from a point contact model with friction. These three-dimensional force-closure conditions are then transformed into two-dimensional plane conditions, leading to a simple algorithm for multi-finger force-closure determination. This method is purely based on geometric analysis, resulting in low computational demands and enabling the rapid assessment of force-closure grasps, which are beneficial for real-time applications. Finally, the algorithm is validated through two case studies, demonstrating its feasibility and effectiveness. Full article

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

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16 pages, 1179 KiB

Open AccessReview

The Role of the Pancreatic Extracellular Matrix as a Tissue Engineering Support for the Bioartificial Pancreas

by Thamires Santos da Silva, Leandro Norberto da Silva-Júnior, Bianca de Oliveira Horvath-Pereira, Maria Carolina Miglino Valbão, Matheus Henrique Herminio Garcia, Juliana Barbosa Lopes, Carlos Henrique Bertoni Reis, Rodrigo da Silva Nunes Barreto, Daniela Vieira Buchaim, Rogerio Leone Buchaim and Maria Angelica Miglino

Biomimetics 2024, 9(10), 598; https://doi.org/10.3390/biomimetics9100598 - 2 Oct 2024

Type 1 diabetes mellitus (T1DM) is a chronic condition primarily managed with insulin replacement, leading to significant treatment costs. Complications include vasculopathy, cardiovascular diseases, nephropathy, neuropathy, and reticulopathy. Pancreatic islet transplantation is an option but its success does not depend solely on adequate [...] Read more.

Type 1 diabetes mellitus (T1DM) is a chronic condition primarily managed with insulin replacement, leading to significant treatment costs. Complications include vasculopathy, cardiovascular diseases, nephropathy, neuropathy, and reticulopathy. Pancreatic islet transplantation is an option but its success does not depend solely on adequate vascularization. The main limitations to clinical islet transplantation are the scarcity of human pancreas, the need for immunosuppression, and the inadequacy of the islet isolation process. Despite extensive research, T1DM remains a major global health issue. In 2015, diabetes affected approximately 415 million people, with projected expenditures of USD 1.7 trillion by 2030. Pancreas transplantation faces challenges due to limited organ availability and complex vascularization. T1DM is caused by the autoimmune destruction of insulin-producing pancreatic cells. Advances in biomaterials, particularly the extracellular matrix (ECM), show promise in tissue reconstruction and transplantation, offering structural and regulatory functions critical for cell migration, differentiation, and adhesion. Tissue engineering aims to create bioartificial pancreases integrating insulin-producing cells and suitable frameworks. This involves decellularization and recellularization techniques to develop biological scaffolds. The challenges include replicating the pancreas’s intricate architecture and maintaining cell viability and functionality. Emerging technologies, such as 3D printing and advanced biomaterials, have shown potential in constructing bioartificial organs. ECM components, including collagens and glycoproteins, play essential roles in cell adhesion, migration, and differentiation. Clinical applications focus on developing functional scaffolds for transplantation, with ongoing research addressing immunological responses and long-term efficacy. Pancreatic bioengineering represents a promising avenue for T1DM treatment, requiring further research to ensure successful implementation. Full article

(This article belongs to the Special Issue Advancements in Regenerative Medicine: An Integrated Approach Using Nanotechnology and 3D Culture Platforms)

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13 pages, 4803 KiB

Open AccessArticle

Design and Demonstration of Hingeless Pneumatic Actuators Inspired by Plants

by Xiangli Zeng, Yingzhe Wang and Keisuke Morishima

Biomimetics 2024, 9(10), 597; https://doi.org/10.3390/biomimetics9100597 - 1 Oct 2024

Soft robots have often been proposed for medical applications, creating human-friendly machines, and dedicated subject operation, and the pneumatic actuator is a representative example of such a robot. Plants, with their hingeless architecture, can take advantage of morphology to achieve a predetermined deformation. [...] Read more.

Soft robots have often been proposed for medical applications, creating human-friendly machines, and dedicated subject operation, and the pneumatic actuator is a representative example of such a robot. Plants, with their hingeless architecture, can take advantage of morphology to achieve a predetermined deformation. To improve the modes of motion, two pneumatic actuators that mimic the principles of the plants (the birds-of-paradise plant and the waterwheel plant) were designed, simulated, and tested using physical models in this study. The most common deformation pattern of the pneumatic actuator, bending deformation, was utilized and hingeless structures based on the plants were fabricated for a more complex motion of the lobes. Here, an ABP (actuator inspired by the birds-of-paradise plant) could bend its midrib downward to open the lobes, but an AWP (actuator inspired by the waterwheel plant) could bend its midrib upward to open the two lobes. In both the computational and physical models, the associated movements of the midrib and lobes could be observed and measured. As it lacks multiple parts that have to be assembled using joints, the actuator would be simpler to fabricate, have a variety of deformation modes, and be applicable in more fields. Full article

(This article belongs to the Special Issue The Latest Progress in Bionics Research)

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