Biomimetics

14 pages, 6225 KiB

Open AccessArticle

The Contribution of the Limbus and Collagen Fibrils to Corneal Biomechanical Properties: Estimation of the Low-Strain In Vivo Elastic Modulus and Tissue Strain

by Frederick H. Silver, Tanmay Deshmukh, Dominick Benedetto, Mickael Asfaw, Olivia Doyle, Nicholas Kozachuk and Kamryn Li

Biomimetics 2024, 9(12), 758; https://doi.org/10.3390/biomimetics9120758 - 13 Dec 2024

Abstract

We have compared the biomechanical properties of human and porcine corneas using vibrational optical coherence tomography (VOCT). The elastic modulus of the cornea has been previously reported in the literature to vary from about several kPa to more than several GPa based on [...] Read more.

We have compared the biomechanical properties of human and porcine corneas using vibrational optical coherence tomography (VOCT). The elastic modulus of the cornea has been previously reported in the literature to vary from about several kPa to more than several GPa based on the results of different techniques. In addition, the formation of corneal cones near the central cornea in keratoconus has been observed in the clinic. Measurements of the resonant frequency and morphology of human and porcine corneas were used to evaluate the role of the limbus in corneal stabilization, the effect of Bowman’s layer, and the effect of collagen content on the low-strain corneal biomechanics. The results of these studies indicate that limbus stability plays an important anatomic role in preventing folding, corneal slippage, and cone formation. Machine learning studies of both human and porcine corneas indicate that Bowman’s membrane, like that of the collagen fibrils found in the anterior corneal stroma, contributes to the 110–120 Hz resonant frequency peak. Finite element and SOLIDWORKS models of normal and keratoconus corneas suggest that the deformation of the cornea is the highest at the central zone and is higher in keratoconus corneas compared to normal controls. VOCT results suggest that although collagen fibril slippage occurs first at the limbus, cone formation in keratoconus occurs centrally/paracentrally, where stress concentration and deformation due to intraocular forces are the highest. Cone formation occurs at the points of maximum curvature. Results of these studies indicate the elastic modulus of cornea fibrillar collagen dictates the corneal elastic modulus at low strains. These results suggest that tension in the cornea at the limbus results in deformation into the low modulus region of the J-shaped stress–strain curve, resulting in an in vivo strain of less than about 10%. We propose that tension in the cornea provides a baseline force that regulates corneal epithelial regeneration as well as corneal lamellae composition and matrix turnover. Full article

(This article belongs to the Special Issue Dynamical Response of Biological System and Biomaterial 2024)

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26 pages, 2478 KiB

Open AccessArticle

Enhanced Nutcracker Optimization Algorithm with Hyperbolic Sine–Cosine Improvement for UAV Path Planning

by Shuhao Jiang, Shengliang Cui, Haoran Song, Yizi Lu and Yong Zhang

Biomimetics 2024, 9(12), 757; https://doi.org/10.3390/biomimetics9120757 - 12 Dec 2024

Abstract

Three-dimensional (3D) path planning is a crucial technology for ensuring the efficient and safe flight of UAVs in complex environments. Traditional path planning algorithms often find it challenging to navigate complex obstacle environments, making it challenging to quickly identify the optimal path. To [...] Read more.

Three-dimensional (3D) path planning is a crucial technology for ensuring the efficient and safe flight of UAVs in complex environments. Traditional path planning algorithms often find it challenging to navigate complex obstacle environments, making it challenging to quickly identify the optimal path. To address these challenges, this paper introduces a Nutcracker Optimizer integrated with Hyperbolic Sine–Cosine (ISCHNOA). First, the exploitation process of the sinh cosh optimizer is incorporated into the foraging strategy to enhance the efficiency of nutcracker in locating high-quality food sources within the search area. Secondly, a nonlinear function is designed to improve the algorithm’s convergence speed. Finally, a sinh cosh optimizer that incorporates historical positions and dynamic factors is introduced to enhance the influence of the optimal position on the search process, thereby improving the accuracy of the nutcracker in retrieving stored food. In this paper, the performance of the ISCHNOA algorithm is tested using 14 classical benchmark test functions as well as the CEC2014 and CEC2020 suites and applied to UAV path planning models. The experimental results demonstrate that the ISCHNOA algorithm outperforms the other algorithms across the three test suites, with the total cost of the planned UAV paths being lower. Full article

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18 pages, 4484 KiB

Open AccessArticle

One-Step Fabrication Process of Silica–Titania Superhydrophobic UV-Blocking Thin Coatings onto Polymeric Films

by Sharon Hayne, Naftali Kanovsky and Shlomo Margel

Biomimetics 2024, 9(12), 756; https://doi.org/10.3390/biomimetics9120756 - 12 Dec 2024

Abstract

Developing a durable multifunctional superhydrophobic coating on polymeric films that can be industrially scalable is a challenge in the field of surface engineering. This article presents a novel method for a scalable technology using a simple single-step fabrication of a superhydrophobic coating on [...] Read more.

Developing a durable multifunctional superhydrophobic coating on polymeric films that can be industrially scalable is a challenge in the field of surface engineering. This article presents a novel method for a scalable technology using a simple single-step fabrication of a superhydrophobic coating on polymeric films that exhibits excellent water-repelling and UV-blocking properties, along with impressive wear resistance and chemical robustness. A mixture of titanium precursors, tetraethylorthosilicate (TEOS), hydrophobic silanes and silica nano/micro-particles is polymerized directly on a corona-treated polymeric film which reacts with the surface via siloxane chemistry. The mixture is then spread on polymeric films using a Mayer rod, which eliminates the need for expensive equipment or multistep processes. The incorporation of silica nanoparticles along with titanium precursor and TEOS results in the formation of a silica–titania network around the silica nanoparticles. This chemically binds them to the activated surface, forming a unique dual-scale surface morphology depending on the size of the silica nanoparticles used in the coating mixture. The coated films were shown to be superhydrophobic with a high water contact angle of over 180° and a rolling angle of 0°. This is due to the combination of dual-scale micro/nano roughness with fluorinated hydrocarbons that lowered the surface free energy. The coatings exhibited excellent chemical and mechanical durability, as well as UV-blocking capabilities. The results show that the coatings remain superhydrophobic even after a sandpaper abrasion test under a pressure of 2.5 kPa for a distance of 30 m. Full article

(This article belongs to the Special Issue Superhydrophobic Surfaces: Challenges, Solutions and Applications)

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19 pages, 954 KiB

Open AccessArticle

Memory–Non-Linearity Trade-Off in Distance-Based Delay Networks

by Stefan Iacob and Joni Dambre

Biomimetics 2024, 9(12), 755; https://doi.org/10.3390/biomimetics9120755 - 11 Dec 2024

Abstract

The performance of echo state networks (ESNs) in temporal pattern learning tasks depends both on their memory capacity (MC) and their non-linear processing. It has been shown that linear memory capacity is maximized when ESN neurons have linear activation, and that a trade-off [...] Read more.

The performance of echo state networks (ESNs) in temporal pattern learning tasks depends both on their memory capacity (MC) and their non-linear processing. It has been shown that linear memory capacity is maximized when ESN neurons have linear activation, and that a trade-off between non-linearity and linear memory capacity is required for temporal pattern learning tasks. The more recent distance-based delay networks (DDNs) have shown improved memory capacity over ESNs in several benchmark temporal pattern learning tasks. However, it has not thus far been studied whether this increased memory capacity comes at the cost of reduced non-linear processing. In this paper, we advance the hypothesis that DDNs in fact achieve a better trade-off between linear MC and non-linearity than ESNs, by showing that DDNs can have strong non-linearity with large memory spans. We tested this hypothesis using the NARMA-30 task and the bitwise delayed XOR task, two commonly used reservoir benchmark tasks that require a high degree of both non-linearity and memory. Full article

(This article belongs to the Special Issue Biomimetics and Bioinspired Artificial Intelligence Applications: 2nd Edition)

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21 pages, 19119 KiB

Open AccessArticle

Caterpillar-Inspired Multi-Gait Generation Method for Series-Parallel Hybrid Segmented Robot

by Mingyuan Dou, Ning He, Jianhua Yang, Lile He, Jiaxuan Chen and Yaojiumin Zhang

Biomimetics 2024, 9(12), 754; https://doi.org/10.3390/biomimetics9120754 - 11 Dec 2024

Abstract

The body structures and motion stability of worm-like and snake-like robots have garnered significant research interest. Recently, innovative serial–parallel hybrid segmented robots have emerged as a fundamental platform for a wide range of motion modes. To address the hyper-redundancy characteristics of these hybrid [...] Read more.

The body structures and motion stability of worm-like and snake-like robots have garnered significant research interest. Recently, innovative serial–parallel hybrid segmented robots have emerged as a fundamental platform for a wide range of motion modes. To address the hyper-redundancy characteristics of these hybrid structures, we propose a novel caterpillar-inspired Stable Segment Update (SSU) gait generation approach, establishing a unified framework for multi-segment robot gait generation. Drawing inspiration from the locomotion of natural caterpillars, the segments are modeled as rigid bodies with six degrees of freedom (DOF). The SSU gait generation method is specifically designed to parameterize caterpillar-like gaits. An inverse kinematics solution is derived by analyzing the forward kinematics and identifying the minimum lifting segment, framing the problem as a single-segment end-effector tracking task. Three distinct parameter sets are introduced within the SSU method to account for the stability of robot motion. These parameters, represented as discrete hump waves, are intended to improve motion efficiency during locomotion. Furthermore, the trajectories for each swinging segment are determined through kinematic analysis. Experimental results validate the effectiveness of the proposed SSU multi-gait generation method, demonstrating the successful traversal of gaps and rough terrain. Full article

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

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11 pages, 4492 KiB

Open AccessArticle

Comparing Polymerization Shrinkage Measurement Methods for Universal Shade Flowable Resin-Based Composites

by Mayumi Maesako, Nicholas G. Fischer, Nagisa Matsui, Amira Elgreatly, Ahmad Mahrous and Akimasa Tsujimoto

Biomimetics 2024, 9(12), 753; https://doi.org/10.3390/biomimetics9120753 - 11 Dec 2024

Abstract

Universal shade flowable composites have been introduced to mimic tooth structure with reduced color mismatch and reduced chair time and cost. However, the polymerization shrinkage of resin material may lead to sensitivity and restoration failure. The purpose of this study was to compare [...] Read more.

Universal shade flowable composites have been introduced to mimic tooth structure with reduced color mismatch and reduced chair time and cost. However, the polymerization shrinkage of resin material may lead to sensitivity and restoration failure. The purpose of this study was to compare the polymerization shrinkage of recently introduced universal shade flowable resin-based composites using both wet and dry density methods. Using two measurement methods, ISO 17304 (wet method) and a gas displacement pycnometry system (dry method), the density of the unpolymerized and the polymerized RBCs were measured, and the polymerization shrinkage was calculated from the density difference. Scanning electron microscopy was used to visualize filler particles. The polymerization shrinkage showed significant differences between many materials. In particular, Bulk Base HARD II Medium Flow showed significantly lower polymerization shrinkage than all the other materials. Shrinkages measured by different methods were significantly different in all cases. The wet method measured a smaller shrinkage than the dry method in most cases, but the shrinkage measured for Gracefil LoFlow was larger with the wet method. Shrinkage between universal shade flowable resin-based composites significantly varied based on both material and measurement method. The polymerization shrinkage of resin-based composites is an important factor in biomimetic clinical dentistry, and work must be conducted to measure it accurately and with more standardization. Full article

(This article belongs to the Special Issue Biomimetic Bonded Restorations for Dental Applications)

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13 pages, 1279 KiB

Open AccessArticle

Predictive Modeling of Hospital Readmission of Schizophrenic Patients in a Spanish Region Combining Particle Swarm Optimization and Machine Learning Algorithms

by Susel Góngora Alonso, Isabel Herrera Montano, Isabel De la Torre Díez, Manuel Franco-Martín, Mohammed Amoon, Jesús-Angel Román-Gallego and María-Luisa Pérez-Delgado

Biomimetics 2024, 9(12), 752; https://doi.org/10.3390/biomimetics9120752 - 11 Dec 2024

Abstract

Readmissions are an indicator of hospital care quality; a high readmission rate is associated with adverse outcomes. This leads to an increase in healthcare costs and quality of life for patients. Developing predictive models for hospital readmissions provides opportunities to select treatments and [...] Read more.

Readmissions are an indicator of hospital care quality; a high readmission rate is associated with adverse outcomes. This leads to an increase in healthcare costs and quality of life for patients. Developing predictive models for hospital readmissions provides opportunities to select treatments and implement preventive measures. The aim of this study is to develop predictive models for the readmission risk of patients with schizophrenia, combining the particle swarm optimization (PSO) algorithm with machine learning classification algorithms. The database used in the study includes a total of 6089 readmission records of patients with schizophrenia. These records were collected from 11 public hospitals in Castilla and León, Spain, in the period 2005–2015. The results of the study show that the Random Forest algorithm combined with PSO achieved the best results across the evaluated performance metrics: AUC = 0.860, recall = 0.959, accuracy = 0.844, and F1-score = 0.907. The development of these new models contributes to -improving patient care. Additionally, they enable preventive measures to reduce costs in healthcare systems. Full article

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

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16 pages, 3208 KiB

Open AccessArticle

Biomimetic Strategies of Slip Sensing, Perception, and Protection in Prosthetic Hand Grasp

by Anran Xie, Zhuozhi Zhang, Jie Zhang, Tie Li, Weidong Chen, James Patton and Ning Lan

Biomimetics 2024, 9(12), 751; https://doi.org/10.3390/biomimetics9120751 - 11 Dec 2024

Abstract

This study develops biomimetic strategies for slip prevention in prosthetic hand grasps. The biomimetic system is driven by a novel slip sensor, followed by slip perception and preventive control. Here, we show that biologically inspired sensorimotor pathways can be restored between the prosthetic [...] Read more.

This study develops biomimetic strategies for slip prevention in prosthetic hand grasps. The biomimetic system is driven by a novel slip sensor, followed by slip perception and preventive control. Here, we show that biologically inspired sensorimotor pathways can be restored between the prosthetic hand and users. A Ruffini endings-like slip sensor is used to detect shear forces and identify slip events directly. The slip information and grip force are encoded into a bi-state sensory coding that evokes vibration and buzz tactile sensations in subjects with transcutaneous electrical nerve stimulation (TENS). Subjects perceive slip events under various conditions based on the vibration sensation and voluntarily adjust grip force to prevent further slipping. Additionally, short-latency compensation for grip force is also implemented using a neuromorphic reflex pathway. The reflex loop includes a sensory neuron and interneurons to adjust the activations of antagonistic muscles reciprocally. The slip prevention system is tested in five able-bodied subjects and two transradial amputees with and without reflex compensation. A psychophysical test for perception reveals that the slip can be detected effectively, with a success accuracy of 96.57%. A slip protection test indicates that reflex compensation yields faster grasp adjustments than voluntary action, with a median response time of 0.30 (0.08) s, a rise time of 0.26 (0.03) s, an execution time of 0.56 (0.07) s, and a slip distance of 0.39 (0.10) cm. Prosthetic grip force is highly correlated to that of an intact hand, with a correlation coefficient of 96.85% (2.73%). These results demonstrate that it is feasible to reconstruct slip biomimetic sensorimotor pathways that provide grasp stability for prosthetic users. Full article

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

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20 pages, 9274 KiB

Open AccessArticle

Numerical Simulation on Self-Propulsion Characteristics of Bionic Flexible Foil Considering Ground Wall Effect

by Yongcheng Li, Nan Zhang, Xinyuan Tang, Ziying Pan and Pengfei Xu

Biomimetics 2024, 9(12), 750; https://doi.org/10.3390/biomimetics9120750 - 10 Dec 2024

Abstract

In order to figure out the wall effect on the propulsive property of an auto-propelled foil, the commercial open-source code ANSYS Fluent was employed to numerically evaluate the fluid dynamics of flexible foil under various wall distances. A virtual model of NACA0015 foil [...] Read more.

In order to figure out the wall effect on the propulsive property of an auto-propelled foil, the commercial open-source code ANSYS Fluent was employed to numerically evaluate the fluid dynamics of flexible foil under various wall distances. A virtual model of NACA0015 foil undergoing travelling wavy motion was adopted, and the research object included 2D and 3D models. To capture the foil’s moving boundary, the dynamic grid technique coupled with the overlapping grid was utilized to realize the foil’s positive deformation and passive forward motion. The ground wall effect on fluid dynamics (thrust force, lift force and propulsive efficiency) and the flow structures of travelling wavy foil were analyzed. The numerical results show that the existence of the ground wall is beneficial for the propulsive property of foil. Specifically, the existence of the wall can improve the forward speed and efficiency of foil, with a maximum increase of 13% in moving velocity and a 10.5% increase in propulsive efficiency. The conclusions acquired in the current study are of great significance for the design of bionic UUV. Full article

(This article belongs to the Special Issue Bionic Robotic Fish: 2nd Edition)

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15 pages, 10958 KiB

Open AccessArticle

ARS: AI-Driven Recovery Controller for Quadruped Robot Using Single-Network Model

by Han Sol Kang, Hyun Yong Lee, Ji Man Park, Seong Won Nam, Yeong Woo Son, Bum Su Yi, Jae Young Oh, Jun Ha Song, Soo Yeon Choi, Bo Geun Kim, Hyun Seok Kim and Hyouk Ryeol Choi

Biomimetics 2024, 9(12), 749; https://doi.org/10.3390/biomimetics9120749 - 10 Dec 2024

Abstract

Legged robots, especially quadruped robots, are widely used in various environments due to their advantage in overcoming rough terrains. However, falling is inevitable. Therefore, the ability to overcome a falling state is an essential ability for legged robots. In this paper, we propose [...] Read more.

Legged robots, especially quadruped robots, are widely used in various environments due to their advantage in overcoming rough terrains. However, falling is inevitable. Therefore, the ability to overcome a falling state is an essential ability for legged robots. In this paper, we propose a method to fully recover a quadruped robot from a fall using a single-neural network model. The neural network model is trained in two steps in simulations using reinforcement learning, and then directly applied to AiDIN-VIII, a quadruped robot with 12 degrees of freedom. Experimental results using the proposed method show that the robot can successfully recover from a fall within 5 s in various postures, even when the robot is completely turned over. In addition, we can see that the robot successfully recovers from a fall caused by a disturbance. Full article

(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics: 2nd Edition)

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14 pages, 10490 KiB

Open AccessArticle

Estimation of Spacecraft Angular Velocity Based on the Optical Flow of Star Images Using an Optimized Kalman Filter

by Jiaqian Si, Yanxiong Niu, Haisha Niu, Zixuan Liu and Danni Liu

Biomimetics 2024, 9(12), 748; https://doi.org/10.3390/biomimetics9120748 - 9 Dec 2024

Abstract

Biomimetic vision is a promising method for efficient navigation and perception, showing great potential in modern navigation systems. Optical flow information, which comes from changes in an image on an organism’s retina as it moves relative to objects, is crucial in this process. [...] Read more.

Biomimetic vision is a promising method for efficient navigation and perception, showing great potential in modern navigation systems. Optical flow information, which comes from changes in an image on an organism’s retina as it moves relative to objects, is crucial in this process. Similarly, the star sensor is a critical component to obtain the optical flow for attitude measurement using sequences of star images. Accurate information on angular velocity obtained from star sensors could guarantee the proper functioning of spacecraft in complex environments. In this study, an optimized Kalman filtering method based on the optical flow of star images for spacecraft angular velocity estimation is proposed. The optimized Kalman filtering method introduces an adaptive factor to enhance the adaptability under dynamic conditions and improve the accuracy of angular velocity estimation. This method only requires optical flow from two consecutive star images. In simulation experiments, the proposed method has been compared with the classic Kalman filtering method. The results demonstrate the high precision and robust performance of the proposed method. Full article

(This article belongs to the Special Issue Bionic Imaging and Optical Devices: 2nd Edition)

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13 pages, 2200 KiB

Open AccessArticle

Deep Neural Networks for Accurate Depth Estimation with Latent Space Features

by Siddiqui Muhammad Yasir and Hyunsik Ahn

Biomimetics 2024, 9(12), 747; https://doi.org/10.3390/biomimetics9120747 - 9 Dec 2024

Abstract

Depth estimation plays a pivotal role in advancing human–robot interactions, especially in indoor environments where accurate 3D scene reconstruction is essential for tasks like navigation and object handling. Monocular depth estimation, which relies on a single RGB camera, offers a more affordable solution [...] Read more.

Depth estimation plays a pivotal role in advancing human–robot interactions, especially in indoor environments where accurate 3D scene reconstruction is essential for tasks like navigation and object handling. Monocular depth estimation, which relies on a single RGB camera, offers a more affordable solution compared to traditional methods that use stereo cameras or LiDAR. However, despite recent progress, many monocular approaches struggle with accurately defining depth boundaries, leading to less precise reconstructions. In response to these challenges, this study introduces a novel depth estimation framework that leverages latent space features within a deep convolutional neural network to enhance the precision of monocular depth maps. The proposed model features dual encoder–decoder architecture, enabling both color-to-depth and depth-to-depth transformations. This structure allows for refined depth estimation through latent space encoding. To further improve the accuracy of depth boundaries and local features, a new loss function is introduced. This function combines latent loss with gradient loss, helping the model maintain the integrity of depth boundaries. The framework is thoroughly tested using the NYU Depth V2 dataset, where it sets a new benchmark, particularly excelling in complex indoor scenarios. The results clearly show that this approach effectively reduces depth ambiguities and blurring, making it a promising solution for applications in human–robot interaction and 3D scene reconstruction. Full article

(This article belongs to the Special Issue Biologically Inspired Vision and Image Processing 2024)

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14 pages, 8982 KiB

Open AccessArticle

Control of Corner Separation in Compressor Cascade Using Biomimetic Fish Scales Structure

by Jin-Long Shen and Szu-I Yeh

Biomimetics 2024, 9(12), 746; https://doi.org/10.3390/biomimetics9120746 - 7 Dec 2024

Abstract

In this study, a fish scale structure with low viscous drag was proposed and applied to the suction surface of a compressor cascade to reduce total pressure loss and suppress corner separation, a key source of compressor inefficiency. By using CFD simulations, the [...] Read more.

In this study, a fish scale structure with low viscous drag was proposed and applied to the suction surface of a compressor cascade to reduce total pressure loss and suppress corner separation, a key source of compressor inefficiency. By using CFD simulations, the biomimetic structure was identified and integrated into the cascade design. To evaluate its effects, we analyzed secondary flow structures using 2D projected streamlines, axial velocity density (AVD), and vortex visualization techniques. The results show that the fish scale structure effectively reduces the volume of low-energy fluid by 18.36% and decreases total pressure loss at the outlet by 3.5%. Additionally, the AVD iso-surface proved instrumental in identifying low-energy fluid regions, which correlate closely with total pressure loss distribution. These findings highlight the potential of biomimetic-inspired designs to improve compressor performance by mitigating corner separation and reducing flow losses. Full article

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20 pages, 12255 KiB

Open AccessArticle

A Biomimetic Pose Estimation and Target Perception Strategy for Transmission Line Maintenance UAVs

by Haoze Zhuo, Zhong Yang, Chi Zhang, Nuo Xu, Bayang Xue, Zekun Zhu and Yucheng Xie

Biomimetics 2024, 9(12), 745; https://doi.org/10.3390/biomimetics9120745 - 6 Dec 2024

Abstract

High-voltage overhead power lines serve as the carrier of power transmission and are crucial to the stable operation of the power system. Therefore, it is particularly important to detect and remove foreign objects attached to transmission lines, as soon as possible. In this [...] Read more.

High-voltage overhead power lines serve as the carrier of power transmission and are crucial to the stable operation of the power system. Therefore, it is particularly important to detect and remove foreign objects attached to transmission lines, as soon as possible. In this context, the widespread promotion and application of smart robots in the power industry can help address the increasingly complex challenges faced by the industry and ensure the efficient, economical, and safe operation of the power grid system. This article proposes a bionic-based UAV pose estimation and target perception strategy, which aims to address the lack of pattern recognition and automatic tracking capabilities of traditional power line inspection UAVs, as well as the poor robustness of visual odometry. Compared with the existing UAV environmental perception solutions, the bionic target perception algorithm proposed in this article can efficiently extract point and line features from infrared images and realize the target detection and automatic tracking function of small multi-rotor drones in the power line scenario, with low power consumption. Full article

(This article belongs to the Special Issue Bio-Inspired Design and Control of Unmanned Aerial Vehicles (UAVs): 2nd Edition)

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31 pages, 11115 KiB

Open AccessArticle

Route Optimization for UVC Disinfection Robot Using Bio-Inspired Metaheuristic Techniques

by Mario Peñacoba, Eduardo Bayona, Jesús Enrique Sierra-García and Matilde Santos

Biomimetics 2024, 9(12), 744; https://doi.org/10.3390/biomimetics9120744 - 5 Dec 2024

Abstract

The COVID-19 pandemic highlighted the urgent need for effective surface disinfection solutions, which has led to the use of mobile robots equipped with ultraviolet (UVC) lamps as a promising technology. This study aims to optimize the navigation of differential mobile robots equipped with [...] Read more.

The COVID-19 pandemic highlighted the urgent need for effective surface disinfection solutions, which has led to the use of mobile robots equipped with ultraviolet (UVC) lamps as a promising technology. This study aims to optimize the navigation of differential mobile robots equipped with UVC lamps to ensure maximum efficiency in disinfecting complex environments. Bio-inspired metaheuristic algorithms such as the gazelle optimization algorithm, whale optimization algorithm, bat optimization algorithm, and particle swarm optimization are applied. These algorithms mimic behaviors of biological beings such as the evasive maneuvers of gazelles, the spiral hunting patterns of whales, the echolocation of bats, and the collective behavior of flocks of birds or schools of fish to optimize the robot’s trajectory. The optimization process adjusts the robot’s coordinates and the time it takes to stops at key points to ensure complete disinfection coverage and minimize the risk of excessive UVC exposure. Experimental results show that the proposed algorithms effectively adapt the robot’s trajectory to various environments, avoiding obstacles and providing sufficient UVC radiation exposure to deactivate target microorganisms. This approach demonstrates the flexibility and robustness of these solutions, with potential applications extending beyond COVID-19 to other pathogens such as influenza or bacterial contaminants, by tuning the algorithm parameters. The results highlight the potential of bio-inspired metaheuristic algorithms to improve automatic disinfection and achieve safer and healthier environments. Full article

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

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17 pages, 11372 KiB

Open AccessArticle

Biodegradation and Thermomechanical Behavior of 3D-Printed PLA Scaffolds Under Static and Stirring Biomimetic Conditions

by Diana V. Portan, Georgios Bampounis, Athanasia Koliadima, Anastasios C. Patsidis, Lykourgos C. Kontaxis and George C. Papanicolaou

Biomimetics 2024, 9(12), 743; https://doi.org/10.3390/biomimetics9120743 - 5 Dec 2024

Abstract

3D-printed biomedical polylactic acid (PLA) scaffolds were developed, and their biodegradation, as well as their thermomechanical behavior, were studied in a relevant in vitro environment. The scaffold’s biodegradability profile has been monitored after immersion in a cell culture medium that contains components of [...] Read more.

3D-printed biomedical polylactic acid (PLA) scaffolds were developed, and their biodegradation, as well as their thermomechanical behavior, were studied in a relevant in vitro environment. The scaffold’s biodegradability profile has been monitored after immersion in a cell culture medium that contains components of blood and body fluids. Two types of biodegradation experiments were performed—a standard static one and an adapted stirring one, mimicking the body fluids’ flow, respectively—to achieve a comparative investigation. The biodegradation experiment’s duration was one month. The measurements were performed between days 1 and 28. The scaffold microstructure was analyzed with scanning electron microscopy (SEM). The weight loss of the scaffolds has been monitored. Differential scanning calorimetry (DSC) has been used to evaluate the glass transition temperature (T_g) of the scaffolds and to draw useful conclusions about their thermal behavior. Finally, dynamic mechanical analysis (DMA) was applied to investigate the viscoelastic behavior of the samples. The SEM analysis demonstrated that the samples in a static experiment are more damaged, while those in the stirring experiment are more brittle. The maximum T_g value of the material measured by DSC is around 65 °C. This value is reached after 5 days of immersion in static conditions and after 14 days of immersion after stirring, indicating that some processes take place faster in the static experiment. The variation of the T_g vs. immersion time, as derived from DSC vs. DMA measurements, gives similar results for both static and fluid absorption conditions, demonstrating the reproducibility of the results. Full article

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22 pages, 9626 KiB

Open AccessArticle

Design of an Active–Passive Composite Impedance Controller for a Soft Robotic Arm Under Contact Constraints

by Bo Yan, Yinglong Chen, Cheng Zhou, Qiang Sun, Fei Gao, Xinyu Yang and Xingtian Xiao

Biomimetics 2024, 9(12), 742; https://doi.org/10.3390/biomimetics9120742 - 5 Dec 2024

Abstract

The inherent passive impedance characteristics of soft robotic arms provide excellent environmental adaptability. When a soft robotic arm interacts with its surroundings, its passive impedance responds swiftly, preventing rigid collisions that could damage the arm and ensuring high safety. However, during the movement [...] Read more.

The inherent passive impedance characteristics of soft robotic arms provide excellent environmental adaptability. When a soft robotic arm interacts with its surroundings, its passive impedance responds swiftly, preventing rigid collisions that could damage the arm and ensuring high safety. However, during the movement of the soft robotic arm, these passive impedance properties are uncontrollable, making it impossible to achieve precise impedance control in constrained environments by relying solely on passive mechanisms. Therefore, this paper integrated active impedance control with the passive impedance characteristics of soft robotic arms, proposing an active–passive composite impedance controller. Additionally, a position-based impedance controller was designed for comparative analysis. Finally, this article developed both control systems and conducted simulations and experiments, demonstrating that the composite active–passive impedance controller offers superior control performance and environmental adaptability. Full article

(This article belongs to the Special Issue Design and Control of a Bio-Inspired Robot: 3rd Edition)

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14 pages, 3527 KiB

Open AccessArticle

Enhanced Foot Proprioception Through 3-Minute Walking Bouts with Ultra-Minimalist Shoes on Surfaces That Mimic Highly Rugged Natural Terrains

by Andrea Biscarini, Andrea Calandra, Alberto Marcucci, Roberto Panichi and Angelo Belotti

Biomimetics 2024, 9(12), 741; https://doi.org/10.3390/biomimetics9120741 - 5 Dec 2024

Abstract

The use of minimalist shoes can lead to enhanced foot somatosensory activation and postural stability but can also increase the incidence of overuse injuries during high-impact or prolonged activities. Therefore, it appears useful to explore new strategies that employ minimalist shoes to effectively [...] Read more.

The use of minimalist shoes can lead to enhanced foot somatosensory activation and postural stability but can also increase the incidence of overuse injuries during high-impact or prolonged activities. Therefore, it appears useful to explore new strategies that employ minimalist shoes to effectively facilitate the somatosensory activation of the foot while minimizing acute and cumulative joint stress and risk of injury. To this purpose, this study introduces a novel exercise paradigm: walking for three minutes in ultra-minimalist shoes on artificial flat surfaces designed to mimic highly rugged natural terrains. The activity of foot muscles and lumbar multifidus, pain perception level, and stabilometric parameters were recorded and analyzed to characterize the novel exercise, comparing it to walking barefoot or in conventional shoes on the same rugged surface. Compared to being barefoot, ultra-minimalist shoes effectively filter nociceptive stimuli from the rugged surface, while compared to conventional shoes, they enhance the somatosensory input supporting static stability. Walking with ultra-minimalist and conventional shoes yielded higher gastrocnemius activity and lower tibialis anterior and multifidus activity compared to barefoot walking. This study highlights a practical and safe framework for enhancing foot somatosensory activation and postural stability. The new intervention is suitable for people of all ages, requires minimal time commitment, and can be performed in controlled environments such as homes, gyms, and healthcare facilities. Full article

(This article belongs to the Section Biomimetic Design, Constructions and Devices)

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15 pages, 6968 KiB

Open AccessArticle

Biomimetic Active Stereo Camera System with Variable FOV

by Yanmiao Zhou and Xin Wang

Biomimetics 2024, 9(12), 740; https://doi.org/10.3390/biomimetics9120740 - 4 Dec 2024

Abstract

Inspired by the biological eye movements of fish such as pipefish and sandlances, this paper presents a novel dynamic calibration method specifically for active stereo vision systems to address the challenges of active cameras with varying fields of view (FOVs). By integrating static [...] Read more.

Inspired by the biological eye movements of fish such as pipefish and sandlances, this paper presents a novel dynamic calibration method specifically for active stereo vision systems to address the challenges of active cameras with varying fields of view (FOVs). By integrating static calibration based on camera rotation angles with dynamic updates of extrinsic parameters, the method leverages relative pose adjustments between the rotation axis and cameras to update extrinsic parameters continuously in real-time. It facilitates epipolar rectification as the FOV changes, and enables precise disparity computation and accurate depth information acquisition. Based on the dynamic calibration method, we develop a two-DOF bionic active camera system including two cameras driven by motors to mimic the movement of biological eyes; this compact system has a large range of visual data. Experimental results show that the calibration method is effective, and achieves high accuracy in extrinsic parameter calculations during FOV adjustments. Full article

(This article belongs to the Special Issue Design and Control of a Bio-Inspired Robot: 3rd Edition)

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