Biomimetics

16 pages, 3840 KiB

Open AccessArticle

Oxygen-Plasma-Treated Al/TaO_X/Al Resistive Memory for Enhanced Synaptic Characteristics

by Gyeongpyo Kim, Seoyoung Park, Minsuk Koo and Sungjun Kim

Biomimetics 2024, 9(9), 578; https://doi.org/10.3390/biomimetics9090578 - 23 Sep 2024

Cited by 1 | Viewed by 1302

In this study, we investigate the impact of O₂ plasma treatment on the performance of Al/TaO_X/Al-based resistive random-access memory (RRAM) devices, focusing on applications in neuromorphic systems. Comparative analysis using scanning electron microscopy and X-ray photoelectron spectroscopy confirmed the differences [...] Read more.

In this study, we investigate the impact of O₂ plasma treatment on the performance of Al/TaO_X/Al-based resistive random-access memory (RRAM) devices, focusing on applications in neuromorphic systems. Comparative analysis using scanning electron microscopy and X-ray photoelectron spectroscopy confirmed the differences in chemical composition between O₂-plasma-treated and untreated RRAM cells. Direct-current measurements showed that O₂-plasma-treated RRAM cells exhibited significant improvements over untreated RRAM cells, including higher on/off ratios, improved uniformity and distribution, longer retention times, and enhanced durability. The conduction mechanism is investigated by current–voltage (I–V) curve fitting. In addition, paired-pulse facilitation (PPF) is observed using partial short-term memory. Furthermore, 3- and 4-bit weight tuning with auto-pulse-tuning algorithms was achieved to improve the controllability of the synapse weight for the neuromorphic system, maintaining retention times exceeding 10³ s in the multiple states. Neuromorphic simulation with an MNIST dataset is conducted to evaluate the synaptic device. Full article

(This article belongs to the Special Issue Bio-Inspired Data-Driven Methods and Their Applications in Engineering Control, Optimization and AI)

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15 pages, 6865 KiB

Open AccessArticle

Method for Bottle Opening with a Dual-Arm Robot

by Francisco J. Naranjo-Campos, Juan G. Victores and Carlos Balaguer

Biomimetics 2024, 9(9), 577; https://doi.org/10.3390/biomimetics9090577 - 23 Sep 2024

Cited by 1 | Viewed by 2000

Abstract

This paper introduces a novel approach to robotic assistance in bottle opening using the dual-arm robot TIAGo++. The solution enhances accessibility by addressing the needs of individuals with injuries or disabilities who may require help with common manipulation tasks. The aim of this [...] Read more.

This paper introduces a novel approach to robotic assistance in bottle opening using the dual-arm robot TIAGo++. The solution enhances accessibility by addressing the needs of individuals with injuries or disabilities who may require help with common manipulation tasks. The aim of this paper is to propose a method involving vision, manipulation, and learning techniques to effectively address the task of bottle opening. The process begins with the acquisition of bottle and cap positions using an RGB-D camera and computer vision. Subsequently, the robot picks the bottle with one gripper and grips the cap with the other, each by planning safe trajectories. Then, the opening procedure is executed via a position and force control scheme that ensures both grippers follow the unscrewing path defined by the cap thread. Within the control loop, force sensor information is employed to control the vertical axis movements, while gripper rotation control is achieved through a Deep Reinforcement Learning (DRL) algorithm trained to determine the optimal angle increments for rotation. The results demonstrate the successful training of the learning agent. The experiments confirm the effectiveness of the proposed method in bottle opening with the TIAGo++ robot, showcasing the practical viability of the approach. Full article

(This article belongs to the Special Issue Computer-Aided Biomimetics: 2nd Edition)

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22 pages, 2853 KiB

Open AccessArticle

A Reinforced Whale Optimization Algorithm for Solving Mathematical Optimization Problems

by Yunpeng Ma, Xiaolu Wang and Wanting Meng

Biomimetics 2024, 9(9), 576; https://doi.org/10.3390/biomimetics9090576 - 22 Sep 2024

Cited by 3 | Viewed by 2011

Abstract

The whale optimization algorithm has several advantages, such as simple operation, few control parameters, and a strong ability to jump out of the local optimum, and has been used to solve various practical optimization problems. In order to improve its convergence speed and [...] Read more.

The whale optimization algorithm has several advantages, such as simple operation, few control parameters, and a strong ability to jump out of the local optimum, and has been used to solve various practical optimization problems. In order to improve its convergence speed and solution quality, a reinforced whale optimization algorithm (RWOA) was designed. Firstly, an opposition-based learning strategy is used to generate other optima based on the best optimal solution found during the algorithm’s iteration, which can increase the diversity of the optimal solution and accelerate the convergence speed. Secondly, a dynamic adaptive coefficient is introduced in the two stages of prey and bubble net, which can balance exploration and exploitation. Finally, a kind of individual information-reinforced mechanism is utilized during the encircling prey stage to improve the solution quality. The performance of the RWOA is validated using 23 benchmark test functions, 29 CEC-2017 test functions, and 12 CEC-2022 test functions. Experiment results demonstrate that the RWOA exhibits better convergence accuracy and algorithm stability than the WOA on 20 benchmark test functions, 21 CEC-2017 test functions, and 8 CEC-2022 test functions, separately. Wilcoxon’s rank sum test shows that there are significant statistical differences between the RWOA and other algorithms Full article

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37 pages, 11393 KiB

Open AccessArticle

Optimizing Deep Learning Models with Improved BWO for TEC Prediction

by Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang and Kunpeng Zhang

Biomimetics 2024, 9(9), 575; https://doi.org/10.3390/biomimetics9090575 - 22 Sep 2024

Cited by 2 | Viewed by 1457

Abstract

The prediction of total ionospheric electron content (TEC) is of great significance for space weather monitoring and wireless communication. Recently, deep learning models have become increasingly popular in TEC prediction. However, these deep learning models usually contain a large number of hyperparameters. Finding [...] Read more.

The prediction of total ionospheric electron content (TEC) is of great significance for space weather monitoring and wireless communication. Recently, deep learning models have become increasingly popular in TEC prediction. However, these deep learning models usually contain a large number of hyperparameters. Finding the optimal hyperparameters (also known as hyperparameter optimization) is currently a great challenge, directly affecting the predictive performance of the deep learning models. The Beluga Whale Optimization (BWO) algorithm is a swarm intelligence optimization algorithm that can be used to optimize hyperparameters of deep learning models. However, it is easy to fall into local minima. This paper analyzed the drawbacks of BWO and proposed an improved BWO algorithm, named FAMBWO (Firefly Assisted Multi-strategy Beluga Whale Optimization). Our proposed FAMBWO was compared with 11 state-of-the-art swarm intelligence optimization algorithms on 30 benchmark functions, and the results showed that our improved algorithm had faster convergence speed and better solutions on almost all benchmark functions. Then we proposed an automated machine learning framework FAMBWO-MA-BiLSTM for TEC prediction, where MA-BiLSTM is for TEC prediction and FAMBWO for hyperparameters optimization. We compared it with grid search, random search, Bayesian optimization algorithm and beluga whale optimization algorithm. Results showed that the MA-BiLSTM model optimized by FAMBWO is significantly better than the MA-BiLSTM model optimized by grid search, random search, Bayesian optimization algorithm, and BWO. Full article

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27 pages, 4812 KiB

Open AccessReview

Nanoparticles as Drug Delivery Vehicles for People with Cystic Fibrosis

by Eoin Hourihane and Katherine R. Hixon

Biomimetics 2024, 9(9), 574; https://doi.org/10.3390/biomimetics9090574 - 22 Sep 2024

Viewed by 2935

Abstract

Cystic Fibrosis (CF) is a life-shortening, genetic disease that affects approximately 145,000 people worldwide. CF causes a dehydrated mucus layer in the lungs, leading to damaging infection and inflammation that eventually result in death. Nanoparticles (NPs), drug delivery vehicles intended for inhalation, have [...] Read more.

Cystic Fibrosis (CF) is a life-shortening, genetic disease that affects approximately 145,000 people worldwide. CF causes a dehydrated mucus layer in the lungs, leading to damaging infection and inflammation that eventually result in death. Nanoparticles (NPs), drug delivery vehicles intended for inhalation, have become a recent source of interest for treating CF and CF-related conditions, and many formulations have been created thus far. This paper is intended to provide an overview of CF and the effect it has on the lungs, the barriers in using NP drug delivery vehicles for treatment, and three common material class choices for these NP formulations: metals, polymers, and lipids. The materials to be discussed include gold, silver, and iron oxide metallic NPs; polyethylene glycol, chitosan, poly lactic-co-glycolic acid, and alginate polymeric NPs; and lipid-based NPs. The novelty of this review comes from a less specific focus on nanoparticle examples, with the focus instead being on the general theory behind material function, why or how a material might be used, and how it may be preferable to other materials used in treating CF. Finally, this paper ends with a short discussion of the two FDA-approved NPs for treatment of CF-related conditions and a recommendation for the future usage of NPs in people with Cystic Fibrosis (pwCF). Full article

(This article belongs to the Special Issue Functional Biomimetic Materials and Devices for Biomedical Applications: 2nd Edition)

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17 pages, 3860 KiB

Open AccessArticle

Superhydrophobicity, Photocatalytic Self-Cleaning and Biocidal Activity Combined in a Siloxane-ZnO Composite for the Protection of Limestone

by Panagiotis N. Manoudis, Ioannis Zuburtikudis, Georgios Konstantopoulos, Hadil Abu Khalifeh, Christine Kottaridi and Ioannis Karapanagiotis

Biomimetics 2024, 9(9), 573; https://doi.org/10.3390/biomimetics9090573 - 22 Sep 2024

Viewed by 1645

Abstract

The erosion phenomena of the natural stone in cultural heritage are induced by various sources. Consequently, the development of multifunctional protective materials that combine two or more useful properties is an effective strategy in addressing the synergistic effects of various erosion mechanisms. A [...] Read more.

The erosion phenomena of the natural stone in cultural heritage are induced by various sources. Consequently, the development of multifunctional protective materials that combine two or more useful properties is an effective strategy in addressing the synergistic effects of various erosion mechanisms. A multifunctional coating, consisting of a silane-based precursor and zinc oxide (ZnO) nanoparticles (NPs), is produced and tested for the protection of limestone. The hybrid coating combines the following three properties: superhydrophobicity, including water-repellency, photocatalytic self-cleaning and biocidal activity. The relative concentration of the NPs (0.8% w/w), used for the suggested composite coating, is carefully selected according to wetting studies, colourimetric measurements and durability (tape peeling) tests. The non-wetting state is evidenced on the surface of the composite coating by the large contact angle of water drops (≈153°) and the small contact angle hysteresis (≈5°), which gives rise to a physical self-cleaning scenario (lotus effect). The photocatalytic chemical self-cleaning is shown with the removal of methylene blue, induced by UV-A radiation. Moreover, it is shown that the suggested coating hinders the incubation of E. coli and S. aureus, as the inhibitions are 94.8 and 99.9%, respectively. Finally, preliminary studies reveal the chemical stability of the suggested coating. Full article

(This article belongs to the Special Issue Bioinspired Strategies for Composite Coatings)

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28 pages, 5564 KiB

Open AccessArticle

MSBWO: A Multi-Strategies Improved Beluga Whale Optimization Algorithm for Feature Selection

by Zhaoyong Fan, Zhenhua Xiao, Xi Li, Zhenghua Huang and Cong Zhang

Biomimetics 2024, 9(9), 572; https://doi.org/10.3390/biomimetics9090572 - 22 Sep 2024

Cited by 3 | Viewed by 2226

Abstract

Feature selection (FS) is a classic and challenging optimization task in most machine learning and data mining projects. Recently, researchers have attempted to develop more effective methods by using metaheuristic methods in FS. To increase population diversity and further improve the effectiveness of [...] Read more.

Feature selection (FS) is a classic and challenging optimization task in most machine learning and data mining projects. Recently, researchers have attempted to develop more effective methods by using metaheuristic methods in FS. To increase population diversity and further improve the effectiveness of the beluga whale optimization (BWO) algorithm, in this paper, we propose a multi-strategies improved BWO (MSBWO), which incorporates improved circle mapping and dynamic opposition-based learning (ICMDOBL) population initialization as well as elite pool (EP), step-adaptive Lévy flight and spiral updating position (SLFSUP), and golden sine algorithm (Gold-SA) strategies. Among them, ICMDOBL contributes to increasing the diversity during the search process and reducing the risk of falling into local optima. The EP technique also enhances the algorithm′s ability to escape from local optima. The SLFSUP, which is distinguished from the original BWO, aims to increase the rigor and accuracy of the development of local spaces. Gold-SA is introduced to improve the quality of the solutions. The hybrid performance of MSBWO was evaluated comprehensively on IEEE CEC2005 test functions, including a qualitative analysis and comparisons with other conventional methods as well as state-of-the-art (SOTA) metaheuristic approaches that were introduced in 2024. The results demonstrate that MSBWO is superior to other algorithms in terms of accuracy and maintains a better balance between exploration and exploitation. Moreover, according to the proposed continuous MSBWO, the binary MSBWO variant (BMSBWO) and other binary optimizers obtained by the mapping function were evaluated on ten UCI datasets with a random forest (RF) classifier. Consequently, BMSBWO has proven very competitive in terms of classification precision and feature reduction. Full article

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22 pages, 1097 KiB

Open AccessArticle

Virtual Simulation-Based Optimization for Assembly Flow Shop Scheduling Using Migratory Bird Algorithm

by Wen-Bin Zhao, Jun-Han Hu and Zi-Qiao Tang

Biomimetics 2024, 9(9), 571; https://doi.org/10.3390/biomimetics9090571 - 21 Sep 2024

Cited by 1 | Viewed by 1250

Abstract

As industrial informatization progresses, virtual simulation technologies are increasingly demonstrating their potential in industrial applications. These systems utilize various sensors to capture real-time factory data, which are then transmitted to servers via communication interfaces to construct corresponding digital models. This integration facilitates tasks [...] Read more.

As industrial informatization progresses, virtual simulation technologies are increasingly demonstrating their potential in industrial applications. These systems utilize various sensors to capture real-time factory data, which are then transmitted to servers via communication interfaces to construct corresponding digital models. This integration facilitates tasks such as monitoring and prediction, enabling more accurate and convenient production scheduling and forecasting. This is particularly significant for flexible or mixed-flow production modes. Bionic optimization algorithms have demonstrated strong performance in factory scheduling and operations. Centered around these algorithms, researchers have explored various strategies to enhance efficiency and optimize processes within manufacturing environments.This study introduces an efficient migratory bird optimization algorithm designed to address production scheduling challenges in an assembly shop with mold quantity constraints. The research aims to minimize the maximum completion time in a batch flow mixed assembly flow shop scheduling problem, incorporating variable batch partitioning strategies. A tailored virtual simulation framework supports this objective. The algorithm employs a two-stage encoding mechanism for batch partitioning and sequencing, adapted to the unique constraints of each production stage. To enhance the search performance of the neighborhood structure, the study identifies and analyzes optimization strategies for batch partitioning and sequencing, and incorporates an adaptive neighborhood structure adjustment strategy. A competition mechanism is also designed to enhance the algorithm’s optimization efficiency. Simulation experiments of varying scales demonstrate the effectiveness of the variable batch partitioning strategy, showing a 5–6% improvement over equal batch strategies. Results across different scales and parameters confirm the robustness of the algorithm. Full article

(This article belongs to the Special Issue Bio-Inspired Data-Driven Methods and Their Applications in Engineering Control, Optimization and AI)

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26 pages, 20942 KiB

Open AccessArticle

Aerodynamic Noise Simulation of a Super-High-Rise Building Facade with Shark-Like Grooved Skin

by Xueqiang Wang, Guangcai Wen and Yangyang Wei

Biomimetics 2024, 9(9), 570; https://doi.org/10.3390/biomimetics9090570 - 19 Sep 2024

Viewed by 1745

Abstract

The wind-driven aerodynamic noise of super-high-rise building facades not only affects the experience of use inside the building but also reduces the life cycle of building facade materials to some extent. In this paper, we are inspired by the micro-groove structure of shark [...] Read more.

The wind-driven aerodynamic noise of super-high-rise building facades not only affects the experience of use inside the building but also reduces the life cycle of building facade materials to some extent. In this paper, we are inspired by the micro-groove structure of shark skin with damping and noise reduction properties and apply bionic skin to reduce the aerodynamic noise impact of super-high-rise buildings. The aerodynamic noise performance of smooth and super-high-rise building models with bionic grooves is simulated via CFD to investigate the noise reduction performance of different bionic groove patterns, such as I-shape, ∪-shape, V-shape, and ∩-shape patterns, and their corresponding acoustic noise reduction mechanisms. This study showed that the bionic shark groove skin has a certain noise reduction effect, and the I-shaped groove has the best noise reduction effect. By applying bionic skin, the aerodynamic noise of super-high-rise buildings can be effectively reduced to improve the use experience and environmental quality of the buildings and provide a new research idea and application direction for the aerodynamic noise reduction design of building facades. Full article

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

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24 pages, 18927 KiB

Open AccessArticle

Biomimetic Adaptive Building Façade Modeling for Sustainable Urban Freshwater Ecosystems: Integration of Nature’s Water-Harvesting Strategy into Sun-Breakers

by Berkan Kahvecioğlu, Güneş Mutlu Avinç and Semra Arslan Selçuk

Biomimetics 2024, 9(9), 569; https://doi.org/10.3390/biomimetics9090569 - 19 Sep 2024

Cited by 1 | Viewed by 2162

Abstract

Urban freshwater ecosystems have many critical functions, such as providing water to all living things and supporting biodiversity. Factors such as water pollution, increased water consumption, habitat loss, climate change, and drought threaten the health of urban freshwater ecosystems. Looking for solutions to [...] Read more.

Urban freshwater ecosystems have many critical functions, such as providing water to all living things and supporting biodiversity. Factors such as water pollution, increased water consumption, habitat loss, climate change, and drought threaten the health of urban freshwater ecosystems. Looking for solutions to these challenges, this article aims to recycle water and return it to its life cycle using a climate-sensitive water collection strategy. The model focuses on the biomimetic method as a basic strategy. In this regard, the concept of water-harvesting has been examined in detail by conducting a deep literature review, including architecture and engineering disciplines. With all these data obtained, a synthesis/integration study was carried out by developing a model proposal based on adaptive building façade elements to solve the water problems experienced in cities. The model proposal, which is directly related to the titles of “Clean Water and Sanitation (SDG 6)” and “Sustainable Cities and Communities (SDG 11)”, which are among the Sustainable Development Goals (SDGs), aims to provide different perspectives on the disciplines with its superficial and functional features. In this context, it is anticipated that the article will become an indispensable resource for other researchers working on the subject. Full article

(This article belongs to the Special Issue Biomimetic Adaptive Buildings)

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11 pages, 3472 KiB

Open AccessArticle

Influence of Trabecular Bone Presence on Osseodensification Instrumentation: An In Vivo Study in Sheep

by Zachary Stauber, Shangtao Wu, Justin E. Herbert, Amanda Willers, Edmara T. P. Bergamo, Vasudev Vivekanand Nayak, Nicholas A. Mirsky, Arthur Castellano, Sinan K. Jabori, Marcelo V. Parra, Estevam A. Bonfante, Lukasz Witek and Paulo G. Coelho

Biomimetics 2024, 9(9), 568; https://doi.org/10.3390/biomimetics9090568 - 19 Sep 2024

Viewed by 1364

Abstract

Osseodensification enhances the stability of endosteal implants. However, pre-clinical studies utilizing osseodensification instrumentation do not account for the limited presence of trabeculae seen clinically. This study aimed to evaluate the effect of osseodensification instrumentation on osteotomy healing in scenarios with and without the [...] Read more.

Osseodensification enhances the stability of endosteal implants. However, pre-clinical studies utilizing osseodensification instrumentation do not account for the limited presence of trabeculae seen clinically. This study aimed to evaluate the effect of osseodensification instrumentation on osteotomy healing in scenarios with and without the presence of trabecular bone. A ~10 cm incision was made over the hip of twelve sheep. Trabecular bone was surgically removed from twelve sites (one site/animal; negative control (Neg. Ctrl)) and left intact at twelve sites (one site/animal; experimental group (Exp.)). All osteotomies were created using the osseodensification drilling protocol. Each osteotomy received an endosteal implant and was evaluated after 3 or 12 weeks of healing (n = 6 animals/time). Histology revealed increased woven and lamellar bone surrounding the implants in the Exp. group relative to the Neg. Ctrl group. The Exp. group demonstrated the presence of bone fragments, which acted as nucleating sites, thereby enhancing the bone formation and remodeling processes. Bone-to-implant contact (%BIC) and bone area fractional occupancy (%BAFO) were significantly higher in the Exp. group relative to the Neg. Ctrl group both at 3 weeks (p = 0.009 and p = 0.043) and 12 weeks (p = 0.010 and p = 0.008). Osseodensification instrumentation in the presence of trabecular bone significantly improved osseointegration. However, no negative influences such as necrosis, inflammation, microfractures, or dehiscence were observed in the absence/limited presence of trabeculae. Full article

(This article belongs to the Special Issue Biomaterials in Bone Regeneration: Challenges to Guarantee Appropriate Biological Features: 2nd Edition)

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25 pages, 2015 KiB

Open AccessArticle

Enhancing Target Tracking: A Novel Grid-Based Beetle Antennae Search Algorithm and Confusion-Aware Detection

by Yixuan Lu, Chencong Ma and Dechao Chen

Biomimetics 2024, 9(9), 567; https://doi.org/10.3390/biomimetics9090567 - 19 Sep 2024

Viewed by 1099

Abstract

Unmanned aerial vehicle target tracking is a complex task that encounters challenges in scenarios involving limited computing resources, real-time requirements, and target confusion. This research builds on previous work and addresses challenges by proposing a grid-based beetle antennae search algorithm and designing a [...] Read more.

Unmanned aerial vehicle target tracking is a complex task that encounters challenges in scenarios involving limited computing resources, real-time requirements, and target confusion. This research builds on previous work and addresses challenges by proposing a grid-based beetle antennae search algorithm and designing a lightweight multi-target detection and positioning method, which integrates interference-sensing mechanisms and depth information. First, the grid-based beetle antennae search algorithm’s rapid convergence advantage is combined with a secondary search and rollback mechanism, enhancing its search efficiency and ability to escape local extreme areas. Then, the You Only Look Once (version 8) model is employed for target detection, while corner detection, feature point extraction, and dictionary matching introduce a confusion-aware mechanism. This mechanism effectively distinguishes potentially confusing targets within the field of view, enhancing the system’s robustness. Finally, the depth-based localization of the target is performed. To verify the performance of the proposed approach, a series of experiments were conducted on the grid-based beetle antennae search algorithm. Comparisons with four mainstream intelligent search algorithms are provided, with the results showing that the grid-based beetle antennae search algorithm excels in the number of iterations to convergence, path length, and convergence speed. When the algorithm faces non-local extreme-value-area environments, the speed is increased by more than 89%. In comparison with previous work, the algorithm speed is increased by more than 233%. Performance tests on the confusion-aware mechanism by using a self-made interference dataset demonstrate the model’s high discriminative ability. The results also indicate that the model meets the real-time requirements. Full article

(This article belongs to the Special Issue Optimal Design Approaches of Bioinspired Robots)

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11 pages, 855 KiB

Open AccessReview

Human–Robot Intimacy: Acceptance of Robots as Intimate Companions

by Sophia Bertoni, Christian Klaes and Artur Pilacinski

Biomimetics 2024, 9(9), 566; https://doi.org/10.3390/biomimetics9090566 - 19 Sep 2024

Viewed by 3469

Abstract

Depictions of robots as romantic partners for humans are frequent in popular culture. As robots become part of human society, they will gradually assume the role of partners for humans whenever necessary, as assistants, collaborators, or companions. Companion robots are supposed to provide [...] Read more.

Depictions of robots as romantic partners for humans are frequent in popular culture. As robots become part of human society, they will gradually assume the role of partners for humans whenever necessary, as assistants, collaborators, or companions. Companion robots are supposed to provide social contact to those who would not have it otherwise. These companion robots are usually not designed to fulfill one of the most important human needs: the one for romantic and intimate contact. Human–robot intimacy remains a vastly unexplored territory. In this article, we review the state-of-the-art research in intimate robotics. We discuss major issues limiting the acceptance of robots as intimate partners, the public perception of robots in intimate roles, and the possible influence of cross-cultural differences in these domains. We also discuss the possible negative effects human–robot intimacy may have on human–human contact. Most importantly, we propose a new term “intimate companion robots” to reduce the negative connotations of the other terms that have been used so far and improve the social perception of research in this domain. With this article, we provide an outlook on prospects for the development of intimate companion robots, considering the specific context of their use. Full article

(This article belongs to the Special Issue Biomimetic Aspects of Human–Computer Interactions)

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19 pages, 18764 KiB

Open AccessArticle

Unsteady Aerodynamic Forces of Tandem Flapping Wings with Different Forewing Kinematics

by Zengshuang Chen, Yuxin Xie and Xueguang Meng

Biomimetics 2024, 9(9), 565; https://doi.org/10.3390/biomimetics9090565 - 19 Sep 2024

Cited by 3 | Viewed by 1311

Abstract

Dragonflies can independently control the movement of their forewing and hindwing to achieve the desired flight. In comparison with previous studies that mostly considered the same kinematics of the fore- and hindwings, this paper focuses on the aerodynamic interference of three-dimensional tandem flapping [...] Read more.

Dragonflies can independently control the movement of their forewing and hindwing to achieve the desired flight. In comparison with previous studies that mostly considered the same kinematics of the fore- and hindwings, this paper focuses on the aerodynamic interference of three-dimensional tandem flapping wings when the forewing kinematics is different from that of the hindwing. The effects of flapping amplitude (Φ₁), flapping mean angle (

\bar{ϕ_{1}}

), and pitch rotation duration (Δtr₁) of the forewing, together with wing spacing (L) are examined numerically. The results show that Φ₁ and

\bar{ϕ_{1}}

have a significant effect on the aerodynamic forces of the individual and tandem systems, but Δtr₁ has little effect. At a small L, a smaller Φ₁, or larger

\bar{ϕ_{1}}

of the forewing can increase the overall aerodynamic force, but at a large L, smaller Φ₁ or larger

\bar{ϕ_{1}}

can actually decrease the force. The flow field analysis shows that Φ₁ and

\bar{ϕ_{1}}

primarily alter the extent of the impact of the previously revealed narrow channel effect, downwash effect, and wake capture effect, thereby affecting force generation. These findings may provide a direction for designing the performance of tandem flapping wing micro-air vehicles by controlling forewing kinematics. Full article

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

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30 pages, 3252 KiB

Open AccessArticle

Comparisons of Inverse Dynamics Formulations in a Spatial Redundantly Actuated Parallel Mechanism Constrained by Two Point Contact Higher Kinematic Pairs

by Chen Cheng, Xiaojing Yuan, Yenan Li and Jian Liu

Biomimetics 2024, 9(9), 564; https://doi.org/10.3390/biomimetics9090564 - 18 Sep 2024

Viewed by 1101

Abstract

A spatial redundantly actuated parallel mechanism (RAPM) constrained by two point contact higher kinematic pairs (HKPs) has been designed, arising from the inspiration of mastication in human beings: the end effector is the lower jaw, the six kinematic chains are the primary chewing [...] Read more.

A spatial redundantly actuated parallel mechanism (RAPM) constrained by two point contact higher kinematic pairs (HKPs) has been designed, arising from the inspiration of mastication in human beings: the end effector is the lower jaw, the six kinematic chains are the primary chewing muscles, and the constraints at HKPs are the temporomandibular joints. In this paper, firstly, the constrained motions of the mechanism are described in detail; thereafter, five models are formulated by the well-known Newton–Euler’s law, the Lagrangian equations, and the principle of virtual work, to explore its rigid-body inverse dynamics. The symbolic results show that the model structures based on these approaches are quite different: the model via the Newton–Euler law well reflects the nature of the mechanism in terms of the constraint forces from HKPs with six equations and eight unknowns, and the existence of reaction forces at the spherical joints is tightly dependent on the number of kinematic chains. In comparison, from the latter two methods, the constraint forces and the reaction forces at spherical joints do not appear in the four models in which there are only four equations and six unknowns. Further, by using the dynamics model of the non-redundantly actuated counterpart as the core in both the second models from the energy and virtual work-related methods, their computational cost is only about 16.7% and 36.63% of the two first models, respectively. Finally, the comparisons between the dynamics models of the RAPM and its counterpart clarify that the HKP constraints greatly alter the model structures and raise the technical difficulties. Full article

(This article belongs to the Special Issue Bioinspired Structures for Soft Actuators)

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25 pages, 7149 KiB

Open AccessArticle

Deep Learning-Based Biomimetic Identification Method for Mask Wearing Standardization

by Bin Yan, Xiameng Li and Wenhui Yan

Biomimetics 2024, 9(9), 563; https://doi.org/10.3390/biomimetics9090563 - 18 Sep 2024

Cited by 2 | Viewed by 1383

Abstract

Deep learning technology can automatically learn features from large amounts of data, with powerful feature extraction and pattern recognition capabilities, thereby improving the accuracy and efficiency of object detection. [The objective of this study]: In order to improve the accuracy and speed of [...] Read more.

Deep learning technology can automatically learn features from large amounts of data, with powerful feature extraction and pattern recognition capabilities, thereby improving the accuracy and efficiency of object detection. [The objective of this study]: In order to improve the accuracy and speed of mask wearing deep learning detection models in the post pandemic era, the [Problem this study aimed to resolve] was based on the fact that no research work has been reported on standardized detection models for mask wearing with detecting nose targets specially. [The topic and method of this study]: A mask wearing normalization detection model (towards the wearing style exposing the nose to outside, which is the most obvious characteristic of non-normalized style) based on improved YOLOv5s (You Only Look Once v5s is an object detection network model) was proposed. [The improved method of the proposed model]: The improvement design work of the detection model mainly includes (1) the BottleneckCSP (abbreviation of Bottleneck Cross Stage Partial) module was improved to a BottleneckCSP-MASK (abbreviation of Bottleneck Cross Stage Partial-MASK) module, which was utilized to replace the BottleneckCSP module in the backbone architecture of the original YOLOv5s model, which reduced the weight parameters’ number of the YOLOv5s model while ensuring the feature extraction effect of the bonding fusion module. (2) An SE module was inserted into the proposed improved model, and the bonding fusion layer in the original YOLOv5s model was improved for better extraction of the features of mask and nose targets. [Results and validation]: The experimental results indicated that, towards different people and complex backgrounds, the proposed mask wearing normalization detection model can effectively detect whether people are wearing masks and whether they are wearing masks in a normalized manner. The overall detection accuracy was 99.3% and the average detection speed was 0.014 s/pic. Contrasted with original YOLOv5s, v5m, and v5l models, the detection results for two types of target objects on the test set indicated that the mAP of the improved model increased by 0.5%, 0.49%, and 0.52%, respectively, and the size of the proposed model compressed by 10% compared to original v5s model. The designed model can achieve precise identification for mask wearing behaviors of people, including not wearing a mask, normalized wearing, and wearing a mask non-normalized. Full article

(This article belongs to the Special Issue Nature-Inspired Metaheuristic Optimization Algorithms 2024)

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24 pages, 10077 KiB

Open AccessArticle

Emotion Recognition Using EEG Signals through the Design of a Dry Electrode Based on the Combination of Type 2 Fuzzy Sets and Deep Convolutional Graph Networks

by Shokoufeh Mounesi Rad and Sebelan Danishvar

Biomimetics 2024, 9(9), 562; https://doi.org/10.3390/biomimetics9090562 - 18 Sep 2024

Cited by 2 | Viewed by 2180

Abstract

Emotion is an intricate cognitive state that, when identified, can serve as a crucial component of the brain–computer interface. This study examines the identification of two categories of positive and negative emotions through the development and implementation of a dry electrode electroencephalogram (EEG). [...] Read more.

Emotion is an intricate cognitive state that, when identified, can serve as a crucial component of the brain–computer interface. This study examines the identification of two categories of positive and negative emotions through the development and implementation of a dry electrode electroencephalogram (EEG). To achieve this objective, a dry EEG electrode is created using the silver-copper sintering technique, which is assessed through Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Analysis (EDXA) evaluations. Subsequently, a database is generated utilizing the designated electrode, which is based on the musical stimulus. The collected data are fed into an improved deep network for automatic feature selection/extraction and classification. The deep network architecture is structured by combining type 2 fuzzy sets (FT2) and deep convolutional graph networks. The fabricated electrode demonstrated superior performance, efficiency, and affordability compared to other electrodes (both wet and dry) in this study. Furthermore, the dry EEG electrode was examined in noisy environments and demonstrated robust resistance across a diverse range of Signal-To-Noise ratios (SNRs). Furthermore, the proposed model achieved a classification accuracy of 99% for distinguishing between positive and negative emotions, an improvement of approximately 2% over previous studies. The manufactured dry EEG electrode is very economical and cost-effective in terms of manufacturing costs when compared to recent studies. The proposed deep network, combined with the fabricated dry EEG electrode, can be used in real-time applications for long-term recordings that do not require gel. Full article

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

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45 pages, 12945 KiB

Open AccessArticle

A Multi-Strategy Improved Northern Goshawk Optimization Algorithm for Optimizing Engineering Problems

by Haijun Liu, Jian Xiao, Yuan Yao, Shiyi Zhu, Yi Chen, Rui Zhou, Yan Ma, Maofa Wang and Kunpeng Zhang

Biomimetics 2024, 9(9), 561; https://doi.org/10.3390/biomimetics9090561 - 16 Sep 2024

Cited by 1 | Viewed by 1869

Abstract

Northern Goshawk Optimization (NGO) is an efficient optimization algorithm, but it has the drawbacks of easily falling into local optima and slow convergence. Aiming at these drawbacks, an improved NGO algorithm named the Multi-Strategy Improved Northern Goshawk Optimization (MSINGO) algorithm was proposed by [...] Read more.

Northern Goshawk Optimization (NGO) is an efficient optimization algorithm, but it has the drawbacks of easily falling into local optima and slow convergence. Aiming at these drawbacks, an improved NGO algorithm named the Multi-Strategy Improved Northern Goshawk Optimization (MSINGO) algorithm was proposed by adding the cubic mapping strategy, a novel weighted stochastic difference mutation strategy, and weighted sine and cosine optimization strategy to the original NGO. To verify the performance of MSINGO, a set of comparative experiments were performed with five highly cited and six recently proposed metaheuristic algorithms on the CEC2017 test functions. Comparative experimental results show that in the vast majority of cases, MSINGO’s exploitation ability, exploration ability, local optimal avoidance ability, and scalability are superior to those of competitive algorithms. Finally, six real world engineering problems demonstrated the merits and potential of MSINGO. Full article

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27 pages, 13890 KiB

Open AccessArticle

A Fast Multi-Scale of Distributed Batch-Learning Growing Neural Gas for Multi-Camera 3D Environmental Map Building

by Chyan Zheng Siow, Azhar Aulia Saputra, Takenori Obo and Naoyuki Kubota

Biomimetics 2024, 9(9), 560; https://doi.org/10.3390/biomimetics9090560 - 16 Sep 2024

Viewed by 1363

Abstract

Biologically inspired intelligent methods have been applied to various sensing systems in order to extract features from a huge size of raw sensing data. For example, point cloud data can be applied to human activity recognition, multi-person tracking, and suspicious person detection, but [...] Read more.

Biologically inspired intelligent methods have been applied to various sensing systems in order to extract features from a huge size of raw sensing data. For example, point cloud data can be applied to human activity recognition, multi-person tracking, and suspicious person detection, but a single RGB-D camera is not enough to perform the above tasks. Therefore, this study propose a 3D environmental map-building method integrating point cloud data measured via multiple RGB-D cameras. First, a fast multi-scale of distributed batch-learning growing neural gas (Fast MS-DBL-GNG) is proposed as a topological feature extraction method in order to reduce computational costs because a single RGB-D camera may output 1 million data. Next, random sample consensus (RANSAC) is applied to integrate two sets of point cloud data using topological features. In order to show the effectiveness of the proposed method, Fast MS-DBL-GNG is applied to perform topological mapping from several point cloud data sets measured in different directions with some overlapping areas included in two images. The experimental results show that the proposed method can extract topological features enough to integrate point cloud data sets, and it runs 14 times faster than the previous GNG method with a 23% reduction in the quantization error. Finally, this paper discuss the advantage and disadvantage of the proposed method through numerical comparison with other methods, and explain future works to improve the proposed method. Full article

(This article belongs to the Special Issue Biomimetics in Intelligent Sensor)

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13 pages, 5413 KiB

Open AccessArticle

Magnetically Driven Quadruped Soft Robot with Multimodal Motion for Targeted Drug Delivery

by Huibin Liu, Xiangyu Teng, Zezheng Qiao, Wenguang Yang and Bentao Zou

Biomimetics 2024, 9(9), 559; https://doi.org/10.3390/biomimetics9090559 - 16 Sep 2024

Cited by 2 | Viewed by 2062

Abstract

Untethered magnetic soft robots show great potential for biomedical and small-scale micromanipulation applications due to their high flexibility and ability to cause minimal damage. However, most current research on these robots focuses on marine and reptilian biomimicry, which limits their ability to move [...] Read more.

Untethered magnetic soft robots show great potential for biomedical and small-scale micromanipulation applications due to their high flexibility and ability to cause minimal damage. However, most current research on these robots focuses on marine and reptilian biomimicry, which limits their ability to move in unstructured environments. In this work, we design a quadruped soft robot with a magnetic top cover and a specific magnetization angle, drawing inspiration from the common locomotion patterns of quadrupeds in nature and integrating our unique actuation principle. It can crawl and tumble and, by adjusting the magnetic field parameters, it adapts its locomotion to environmental conditions, enabling it to cross obstacles and perform remote transportation and release of cargo. Full article

(This article belongs to the Special Issue Bio-Inspired Soft Robotics: Design, Fabrication and Applications)

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27 pages, 7597 KiB

Open AccessArticle

A Method for Assessing the Reliability of the Pepper Robot in Handling Office Documents: A Case Study

by Marius Misaroș, Ovidiu Petru Stan, Szilárd Enyedi, Anca Stan, Ionuț Donca and Liviu Cristian Miclea

Biomimetics 2024, 9(9), 558; https://doi.org/10.3390/biomimetics9090558 - 16 Sep 2024

Cited by 1 | Viewed by 2500

Abstract

Humanoid robots are increasingly being utilized in various activities involving humans, as they can facilitate certain tasks and provide benefits to users. Humanoid service robots possess capabilities akin to human performance, often proving advantageous due to their operational speed and immunity to fatigue. [...] Read more.

Humanoid robots are increasingly being utilized in various activities involving humans, as they can facilitate certain tasks and provide benefits to users. Humanoid service robots possess capabilities akin to human performance, often proving advantageous due to their operational speed and immunity to fatigue. Within the scope of this study, Pepper, a humanoid robot renowned for its fidelity in mimicking human gestures and behavior, serves as the focal point. Tasked with aiding office occupants in object manipulation and relocation, Pepper underwent a targeted reliability assessment. This assessment encompassed the development of a reliability block diagram (RBD), alongside meticulous analyses of individual components and system functionality across diverse operational scenarios. Full article

(This article belongs to the Section Locomotion and Bioinspired Robotics)

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27 pages, 9664 KiB

Open AccessArticle

Bio-Inspired Motion Emulation for Social Robots: A Real-Time Trajectory Generation and Control Approach

by Marvin H. Cheng, Po-Lin Huang and Hao-Chuan Chu

Biomimetics 2024, 9(9), 557; https://doi.org/10.3390/biomimetics9090557 - 15 Sep 2024

Viewed by 1620

Abstract

Assistive robotic platforms have recently gained popularity in various healthcare applications, and their use has expanded to social settings such as education, tourism, and manufacturing. These social robots, often in the form of bio-inspired humanoid systems, provide significant psychological and physiological benefits through [...] Read more.

Assistive robotic platforms have recently gained popularity in various healthcare applications, and their use has expanded to social settings such as education, tourism, and manufacturing. These social robots, often in the form of bio-inspired humanoid systems, provide significant psychological and physiological benefits through one-on-one interactions. To optimize the interaction between social robotic platforms and humans, it is crucial for these robots to identify and mimic human motions in real time. This research presents a motion prediction model developed using convolutional neural networks (CNNs) to efficiently determine the type of motions at the initial state. Once identified, the corresponding reactions of the robots are executed by moving their joints along specific trajectories derived through temporal alignment and stored in a pre-selected motion library. In this study, we developed a multi-axial robotic arm integrated with a motion identification model to interact with humans by emulating their movements. The robotic arm follows pre-selected trajectories for corresponding interactions, which are generated based on identified human motions. To address the nonlinearities and cross-coupled dynamics of the robotic system, we applied a control strategy for precise motion tracking. This integrated system ensures that the robotic arm can achieve adequate controlled outcomes, thus validating the feasibility of such an interactive robotic system in providing effective bio-inspired motion emulation. Full article

(This article belongs to the Special Issue Bio-Inspired Approaches—a Leverage for Robotics)

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19 pages, 6591 KiB

Open AccessArticle

Finite-Time Line-of-Sight Guidance-Based Path-Following Control for a Wire-Driven Robot Fish

by Yuyang Mo, Weiheng Su, Zicun Hong, Yunquan Li and Yong Zhong

Biomimetics 2024, 9(9), 556; https://doi.org/10.3390/biomimetics9090556 - 15 Sep 2024

Cited by 2 | Viewed by 1385

Abstract

This paper presents an adaptive line-of-sight (LOS) guidance method, incorporating a finite-time sideslip angle observer to achieve precise planar path tracking of a bionic robotic fish driven by LOS. First, an adaptive LOS guidance method based on real-time cross-track error is presented. To [...] Read more.

This paper presents an adaptive line-of-sight (LOS) guidance method, incorporating a finite-time sideslip angle observer to achieve precise planar path tracking of a bionic robotic fish driven by LOS. First, an adaptive LOS guidance method based on real-time cross-track error is presented. To mitigate the adverse effects of the sideslip angle on tracking performance, a finite-time observer (FTO) based on finite-time convergence theory is employed to observe the time-varying sideslip angle and correct the target yaw. Subsequently, classical proportional–integral–derivative (PID) controllers are utilized to achieve yaw tracking, followed by static and dynamic yaw angle experiments for evaluation. Finally, the yaw-tracking-based path-tracking control strategy is applied to the robotic fish, whose motion is generated by an improved central pattern generator (CPG) and equipped with a six-axis inertial measurement unit for real-time swimming direction. Quantitative comparisons in tank experiments validate the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Bio-Inspired Soft Robotics: Design, Fabrication and Applications)

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18 pages, 16152 KiB

Open AccessArticle

Characterization of Wing Kinematics by Decoupling Joint Movement in the Pigeon

by Yishi Shen, Shi Zhang, Weimin Huang, Chengrui Shang, Tao Sun and Qing Shi

Biomimetics 2024, 9(9), 555; https://doi.org/10.3390/biomimetics9090555 - 15 Sep 2024

Cited by 2 | Viewed by 1966

Abstract

Birds have remarkable flight capabilities due to their adaptive wing morphology. However, studying live birds is time-consuming and laborious, and obtaining information about the complete wingbeat cycle is difficult. To address this issue and provide a complete dataset, we recorded comprehensive motion capture [...] Read more.

Birds have remarkable flight capabilities due to their adaptive wing morphology. However, studying live birds is time-consuming and laborious, and obtaining information about the complete wingbeat cycle is difficult. To address this issue and provide a complete dataset, we recorded comprehensive motion capture wing trajectory data from five free-flying pigeons (Columba livia). Five key motion parameters are used to quantitatively characterize wing kinematics: flapping, sweeping, twisting, folding and bending. In addition, the forelimb skeleton is mapped using an open-chain three-bar mechanism model. By systematically evaluating the relationship of joint degrees of freedom (DOFs), we configured the model as a 3-DOF shoulder, 1-DOF elbow and 2-DOF wrist. Based on the correlation analysis between wingbeat kinematics and joint movement, we found that the strongly correlated shoulder and wrist roll within the stroke plane cause wing flap and bending. There is also a strong correlation between shoulder, elbow and wrist yaw out of the stroke plane, which causes wing sweep and fold. By simplifying the wing morphing, we developed three flapping wing robots, each with different DOFs inside and outside the stroke plane. This study provides insight into the design of flapping wing robots capable of mimicking the 3D wing motion of pigeons. Full article

(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots: Second Edition)

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20 pages, 4335 KiB

Open AccessArticle

Advanced Design and Implementation of a Biomimetic Humanoid Robotic Head Based on Vietnamese Anthropometry

by Nguyen Minh Trieu and Nguyen Truong Thinh

Biomimetics 2024, 9(9), 554; https://doi.org/10.3390/biomimetics9090554 - 15 Sep 2024

Cited by 1 | Viewed by 2172

Abstract

In today’s society, robots are increasingly being developed and playing an important role in many fields of industry. Combined with advances in artificial intelligence, sensors, and design principles, these robots are becoming smarter, more flexible, and especially capable of interacting more naturally with [...] Read more.

In today’s society, robots are increasingly being developed and playing an important role in many fields of industry. Combined with advances in artificial intelligence, sensors, and design principles, these robots are becoming smarter, more flexible, and especially capable of interacting more naturally with humans. In that context, a comprehensive humanoid robot with human-like actions and emotions has been designed to move flexibly like a human, performing movements to simulate the movements of the human neck and head so that the robot can interact with the surrounding environment. The mechanical design of the emotional humanoid robot head focuses on the natural and flexible movement of human electric motors, including flexible suitable connections, precise motors, and feedback signals. The feedback control parts, such as the neck, eyes, eyebrows, and mouth, are especially combined with artificial skin to create a human-like appearance. This study aims to contribute to the field of biomimetic humanoid robotics by developing a comprehensive design for a humanoid robot head with human-like actions and emotions, as well as evaluating the effectiveness of the motor and feedback control system in simulating human behavior and emotional expression, thereby enhancing natural interaction between robots and humans. Experimental results from the survey showed that the behavioral simulation rate reached 94.72%, and the emotional expression rate was 91.50%. Full article

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

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20 pages, 8018 KiB

Open AccessEditor’s ChoiceArticle

Biomimetic Wings for Micro Air Vehicles

by Giorgio Moscato and Giovanni P. Romano

Biomimetics 2024, 9(9), 553; https://doi.org/10.3390/biomimetics9090553 - 14 Sep 2024

Cited by 3 | Viewed by 1546

Abstract

In this work, micro air vehicles (MAVs) equipped with bio-inspired wings are investigated experimentally in wind tunnel. The starting point is that insects such as dragonflies, butterflies and locusts have wings with rigid tubular elements (corrugation) connected by flexible parts (profiling). So far, [...] Read more.

In this work, micro air vehicles (MAVs) equipped with bio-inspired wings are investigated experimentally in wind tunnel. The starting point is that insects such as dragonflies, butterflies and locusts have wings with rigid tubular elements (corrugation) connected by flexible parts (profiling). So far, it is important to understand the specific aerodynamic effects of corrugation and profiling as applied to conventional wings for the optimization of low-Reynolds-number aerodynamics. The present study, in comparison to previous investigations on the topic, considers whole MAVs rather than isolated wings. A planform with a low aperture-to-chord ratio is employed in order to investigate the interaction between large tip vortices and the flow over the wing surface at large angles of incidence. Comparisons are made by measuring global aerodynamic loads using force balance, specifically drag and lift, and detailed local velocity fields over wing surfaces, by means of particle image velocimetry (PIV). This type of combined global–local investigation allows describing and relating overall MAV performance to detailed high-resolution flow fields. The results indicate that the combination of wing corrugation and profiling gives effective enhancements in performance, around 50%, in comparison to the classical flat-plate configuration. These results are particularly relevant in the framework of low-aspect-ratio MAVs, undergoing beneficial interactions between tip vortices and large-scale separation. Full article

(This article belongs to the Special Issue Biomechanics and Biomimetics for Insect-Inspired MAVs)

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30 pages, 8374 KiB

Open AccessArticle

Multi-Strategy Improved Harris Hawk Optimization Algorithm and Its Application in Path Planning

by Chaoli Tang, Wenyan Li, Tao Han, Lu Yu and Tao Cui

Biomimetics 2024, 9(9), 552; https://doi.org/10.3390/biomimetics9090552 - 12 Sep 2024

Cited by 6 | Viewed by 1617

Abstract

Path planning is a key problem in the autonomous navigation of mobile robots and a research hotspot in the field of robotics. Harris Hawk Optimization (HHO) faces challenges such as low solution accuracy and a slow convergence speed, and it easy falls into [...] Read more.

Path planning is a key problem in the autonomous navigation of mobile robots and a research hotspot in the field of robotics. Harris Hawk Optimization (HHO) faces challenges such as low solution accuracy and a slow convergence speed, and it easy falls into local optimization in path planning applications. For this reason, this paper proposes a Multi-strategy Improved Harris Hawk Optimization (MIHHO) algorithm. First, the double adaptive weight strategy is used to enhance the search capability of the algorithm to significantly improve the convergence accuracy and speed of path planning; second, the Dimension Learning-based Hunting (DLH) search strategy is introduced to effectively balance exploration and exploitation while maintaining the diversity of the population; and then, Position update strategy based on Dung Beetle Optimizer algorithm is proposed to reduce the algorithm’s possibility of falling into local optimal solutions during path planning. The experimental results of the comparison of the test functions show that the MIHHO algorithm is ranked first in terms of performance, with significant improvements in optimization seeking ability, convergence speed, and stability. Finally, MIHHO is applied to robot path planning, and the test results show that in four environments with different complexities and scales, the average path lengths of MIHHO are improved by 1.99%, 14.45%, 4.52%, and 9.19% compared to HHO, respectively. These results indicate that MIHHO has significant performance advantages in path planning tasks and helps to improve the path planning efficiency and accuracy of mobile robots. Full article

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13 pages, 2218 KiB

Open AccessArticle

Few-Shot Learning in Wi-Fi-Based Indoor Positioning

by Feng Xie, Soi Hoi Lam, Ming Xie and Cheng Wang

Biomimetics 2024, 9(9), 551; https://doi.org/10.3390/biomimetics9090551 - 12 Sep 2024

Viewed by 1719

Abstract

This paper explores the use of few-shot learning in Wi-Fi-based indoor positioning, utilizing convolutional neural networks (CNNs) combined with meta-learning techniques to enhance the accuracy and efficiency of positioning systems. The focus is on addressing the challenge of limited labeled data, a prevalent [...] Read more.

This paper explores the use of few-shot learning in Wi-Fi-based indoor positioning, utilizing convolutional neural networks (CNNs) combined with meta-learning techniques to enhance the accuracy and efficiency of positioning systems. The focus is on addressing the challenge of limited labeled data, a prevalent issue in extensive indoor environments. The study explores various scenarios, comparing the performance of the base CNN and meta-learning models. The meta-learning approach involves few-shot learning tasks, such as three-way N-shot, five-way N-shot, etc., to enhance the model’s ability to generalize from limited data. The experiments were conducted across various scenarios, evaluating the performance of the models with different numbers of samples per class (K) after filtering by cosine similarity (FCS) during both the stages of data preprocessing and meta-learning. The scenarios included both base classes and novel classes, with and without meta-learning. The results indicated that the base CNN model achieved varying accuracy levels depending on the scenario and the number of samples per class retained after FCS. Meta-learning performed acceptably in scenarios with fewer samples, which are the distinct datasets pertaining to novel classes. With 20 samples per class, the base CNN achieved an accuracy of 0.80 during the pre-training stage, while meta-learning (three-way one-shot) achieved an accuracy of 0.78 on a new small dataset with novel classes. Full article

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21 pages, 8015 KiB

Open AccessArticle

Bionic Robot with Multifunctional Leg–Arm Mechanism for In-Orbit Assembly of Space Trusses

by Yuetian Shi, Qingzhang Xu, Rui Shi, Haohang Liu, Meiyang Zhang, Xuyan Hou, Weijun Wang and Zongquan Deng

Biomimetics 2024, 9(9), 550; https://doi.org/10.3390/biomimetics9090550 - 11 Sep 2024

Cited by 1 | Viewed by 1866

Abstract

This article aims to address the in-orbit assembly needs of truss structures in space missions by designing a robot capable of moving on trusses and manipulating parts. To enhance the stability of the robot during movement and part manipulation, inspiration was drawn from [...] Read more.

This article aims to address the in-orbit assembly needs of truss structures in space missions by designing a robot capable of moving on trusses and manipulating parts. To enhance the stability of the robot during movement and part manipulation, inspiration was drawn from the Dynastes Hercules beetle. Building upon detailed research on the Dynastes Hercules beetle, a biomimetic structure was designed for the robot system. Based on specific task requirements, the overall plan of the robot was developed, and its kinematic and dynamic models were derived. A prototype of the robot was created, which is capable of both movement and assembly functions, including handling spherical and rod-like objects. Through a series of experiments conducted with the robot, the research results demonstrated that the proposed design can effectively achieve the intended functions. Full article

(This article belongs to the Special Issue Recent Advances in Robotics and Biomimetics)

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24 pages, 2183 KiB

Open AccessReview

A Comprehensive Review on Studying and Developing Guidelines to Standardize the Inspection of Properties and Production Methods for Mycelium-Bound Composites in Bio-Based Building Material Applications

by Worawoot Aiduang, Praween Jinanukul, Wandee Thamjaree, Tanongkiat Kiatsiriroat, Tanut Waroonkun and Saisamorn Lumyong

Biomimetics 2024, 9(9), 549; https://doi.org/10.3390/biomimetics9090549 - 11 Sep 2024

Cited by 2 | Viewed by 2173

Abstract

Mycelium-bound composites (MBCs) represent a promising advancement in bio-based building materials, offering sustainable alternatives for engineering and construction applications. This review provides a comprehensive overview of the current research landscape, production methodologies, and standardization ideas related to MBCs. A basic search on Scopus [...] Read more.

Mycelium-bound composites (MBCs) represent a promising advancement in bio-based building materials, offering sustainable alternatives for engineering and construction applications. This review provides a comprehensive overview of the current research landscape, production methodologies, and standardization ideas related to MBCs. A basic search on Scopus revealed over 250 publications on MBCs between 2020 and 2024, with more than 30% focusing on engineering and materials science. Key studies have investigated the physical and mechanical properties of MBCs, optimizing parameters such as substrate type, fungal species, incubation time, and post-processing to enhance material performance. Standardizing the inspection of MBC properties is crucial for ensuring quality and reliability. Various testing standards, including those from the American Society for Testing and Materials (ASTM), the International Organization for Standardization (ISO), the Japanese Industrial Standard (JIS), European Standards (EN), Deutsches Institut für Normung (DIN), and the Thai Industrial Standards Institute (TIS), are utilized to evaluate density, water absorption, compression strength, tensile strength, insulation, and other critical properties. This review highlights the distinction between lab-scale and apply-scale testing methodologies, emphasizing the need for comprehensive evaluation protocols. Additionally, the production process of MBCs involves critical steps like substrate preparation, fungal species selection, and mycelium growth, necessitating the implementation of good manufacturing practices (GMPs) to ensure consistency and quality. The internal and external structures of MBCs significantly influence their performance, necessitating standardized inspection methods using advanced techniques such as scanning electron microscopy (SEM), X-ray computed tomography (CT) scanning, and surface profilometry. By establishing robust inspection protocols and production standards, the industry can enhance the reliability and adoption of MBCs, contributing to innovations in materials science and promoting environmental sustainability. This review underscores the importance of interdisciplinary collaboration, advanced characterization tools, and regulatory frameworks to address challenges and advance the field of MBCs. Full article

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Biomimetics, Volume 9, Issue 9 (September 2024) – 72 articles

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