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Biomimetics
Volume 8
Issue 2
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Biomimetics, Volume 8, Issue 2 (June 2023) – 136 articles

Cover Story (view full-size image): Cells can sense and respond to different kinds of mechanical strains in the body. Mechanical stimulation needs to be included in vitro to more effectively mimic the existing complexity of in vivo systems. In this study, we developed a pneumatically driven fiber robot as a platform for 3D dynamic cell culture. The fiber robot can generate tunable contractions. The surface of the fiber robot is formed by a braiding structure, which provides promising surface contact and adequate space for cell culture. We demonstrated that the dynamic culture system was able to support cell proliferation with minimal cytotoxicity, similar to static culture. In summary, a simple and cost-effective 3D dynamic culture system has been proposed, which can be easily implemented to study complex biological phenomena in vitro. View this paper
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16 pages, 3140 KiB  
Article
Biased Random Walk Model of Neuronal Dynamics on Substrates with Periodic Geometrical Patterns
by Cristian Staii
Biomimetics 2023, 8(2), 267; https://doi.org/10.3390/biomimetics8020267 - 20 Jun 2023
Cited by 1 | Viewed by 1449
Abstract
Neuronal networks are complex systems of interconnected neurons responsible for transmitting and processing information throughout the nervous system. The building blocks of neuronal networks consist of individual neurons, specialized cells that receive, process, and transmit electrical and chemical signals throughout the body. The [...] Read more.
Neuronal networks are complex systems of interconnected neurons responsible for transmitting and processing information throughout the nervous system. The building blocks of neuronal networks consist of individual neurons, specialized cells that receive, process, and transmit electrical and chemical signals throughout the body. The formation of neuronal networks in the developing nervous system is a process of fundamental importance for understanding brain activity, including perception, memory, and cognition. To form networks, neuronal cells extend long processes called axons, which navigate toward other target neurons guided by both intrinsic and extrinsic factors, including genetic programming, chemical signaling, intercellular interactions, and mechanical and geometrical cues. Despite important recent advances, the basic mechanisms underlying collective neuron behavior and the formation of functional neuronal networks are not entirely understood. In this paper, we present a combined experimental and theoretical analysis of neuronal growth on surfaces with micropatterned periodic geometrical features. We demonstrate that the extension of axons on these surfaces is described by a biased random walk model, in which the surface geometry imparts a constant drift term to the axon, and the stochastic cues produce a random walk around the average growth direction. We show that the model predicts key parameters that describe axonal dynamics: diffusion (cell motility) coefficient, average growth velocity, and axonal mean squared length, and we compare these parameters with the results of experimental measurements. Our findings indicate that neuronal growth is governed by a contact-guidance mechanism, in which the axons respond to external geometrical cues by aligning their motion along the surface micropatterns. These results have a significant impact on developing novel neural network models, as well as biomimetic substrates, to stimulate nerve regeneration and repair after injury. Full article
(This article belongs to the Special Issue Bio-Inspired Neural Networks)
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17 pages, 433 KiB  
Article
Binary Restructuring Particle Swarm Optimization and Its Application
by Jian Zhu, Jianhua Liu, Yuxiang Chen, Xingsi Xue and Shuihua Sun
Biomimetics 2023, 8(2), 266; https://doi.org/10.3390/biomimetics8020266 - 17 Jun 2023
Cited by 10 | Viewed by 2254
Abstract
Restructuring Particle Swarm Optimization (RPSO) algorithm has been developed as an intelligent approach based on the linear system theory of particle swarm optimization (PSO). It streamlines the flow of the PSO algorithm, specifically targeting continuous optimization problems. In order to adapt RPSO for [...] Read more.
Restructuring Particle Swarm Optimization (RPSO) algorithm has been developed as an intelligent approach based on the linear system theory of particle swarm optimization (PSO). It streamlines the flow of the PSO algorithm, specifically targeting continuous optimization problems. In order to adapt RPSO for solving discrete optimization problems, this paper proposes the binary Restructuring Particle Swarm Optimization (BRPSO) algorithm. Unlike other binary metaheuristic algorithms, BRPSO does not utilize the transfer function. The particle updating process in BRPSO relies solely on comparison results between values derived from the position updating formula and a random number. Additionally, a novel perturbation term is incorporated into the position updating formula of BRPSO. Notably, BRPSO requires fewer parameters and exhibits high exploration capability during the early stages. To evaluate the efficacy of BRPSO, comprehensive experiments are conducted by comparing it against four peer algorithms in the context of feature selection problems. The experimental results highlight the competitive nature of BRPSO in terms of both classification accuracy and the number of selected features. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)
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10 pages, 5830 KiB  
Article
Biomimetics with Trade-Offs
by Julian Vincent
Biomimetics 2023, 8(2), 265; https://doi.org/10.3390/biomimetics8020265 - 17 Jun 2023
Cited by 2 | Viewed by 1425
Abstract
Our knowledge of physics and chemistry is relatively well defined. Results from that knowledge are predictable as, largely, are those of their technical offspring such as electrical, chemical, mechanical and civil engineering. By contrast, biology is relatively unconstrained and unpredictable. A factor common [...] Read more.
Our knowledge of physics and chemistry is relatively well defined. Results from that knowledge are predictable as, largely, are those of their technical offspring such as electrical, chemical, mechanical and civil engineering. By contrast, biology is relatively unconstrained and unpredictable. A factor common to all areas is the trade-off, which provides a means of defining and quantifying a problem and, ideally, its solution. In order to understand the anatomy of the trade-off and how to handle it, its development (as the dialectic) is tracked from Hegel and Marx to its implementation as dialectical materialism in Russian philosophy and TRIZ, the Theory of Invention. With the ready availability of mathematical techniques, such as multi-objective analysis and the Pareto set, the trade-off is well-adapted to bridging the gaps between the quantified and the unquantifiable, allowing modelling and the transfer of concepts by analogy. It is thus an ideal tool for biomimetics. An intracranial endoscope can be derived with little change from the egg-laying tube of a wood wasp. More complex transfers become available as the technique is developed. Most important, as more trade-offs are analyzed, their results are stored to be used again in the solution of problems. There is no other system in biomimetics which can do this. Full article
(This article belongs to the Special Issue Bio-Inspired Design: Creativity and Innovation)
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19 pages, 8641 KiB  
Article
A High-Efficient Reinforcement Learning Approach for Dexterous Manipulation
by Jianhua Zhang, Xuanyi Zhou, Jinyu Zhou, Shiming Qiu, Guoyuan Liang, Shibo Cai and Guanjun Bao
Biomimetics 2023, 8(2), 264; https://doi.org/10.3390/biomimetics8020264 - 16 Jun 2023
Cited by 1 | Viewed by 2150
Abstract
Robotic hands have the potential to perform complex tasks in unstructured environments owing to their bionic design, inspired by the most agile biological hand. However, the modeling, planning and control of dexterous hands remain unresolved, open challenges, resulting in the simple movements and [...] Read more.
Robotic hands have the potential to perform complex tasks in unstructured environments owing to their bionic design, inspired by the most agile biological hand. However, the modeling, planning and control of dexterous hands remain unresolved, open challenges, resulting in the simple movements and relatively clumsy motions of current robotic end effectors. This paper proposed a dynamic model based on generative adversarial architecture to learn the state mode of the dexterous hand, reducing the model’s prediction error in long spans. An adaptive trajectory planning kernel was also developed to generate High-Value Area Trajectory (HVAT) data according to the control task and dynamic model, with adaptive trajectory adjustment achieved by changing the Levenberg–Marquardt (LM) coefficient and the linear searching coefficient. Furthermore, an improved Soft Actor–Critic (SAC) algorithm is designed by combining maximum entropy value iteration and HVAT value iteration. An experimental platform and simulation program were built to verify the proposed method with two manipulating tasks. The experimental results indicate that the proposed dexterous hand reinforcement learning algorithm has better training efficiency and requires fewer training samples to achieve quite satisfactory learning and control performance. Full article
(This article belongs to the Special Issue Bionic Robot Hand: Dexterous Manipulation and Robust Grasping)
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23 pages, 8417 KiB  
Article
Computational Study of Stiffness-Tuning Strategies in Anguilliform Fish
by Zuo Cui and Xuyao Zhang
Biomimetics 2023, 8(2), 263; https://doi.org/10.3390/biomimetics8020263 - 16 Jun 2023
Cited by 3 | Viewed by 1707
Abstract
Biological evidence demonstrates that fish can tune their body stiffness to improve thrust and efficiency during swimming locomotion. However, the stiffness-tuning strategies that maximize swimming speed or efficiency are still unclear. In the present study, a musculo-skeletal model of anguilliform fish is developed [...] Read more.
Biological evidence demonstrates that fish can tune their body stiffness to improve thrust and efficiency during swimming locomotion. However, the stiffness-tuning strategies that maximize swimming speed or efficiency are still unclear. In the present study, a musculo-skeletal model of anguilliform fish is developed to study the properties of variable stiffness, in which the planar serial-parallel mechanism is used to model the body structure. The calcium ion model is adopted to simulate muscular activities and generate muscle force. Further, the relations among the forward speed, the swimming efficiency, and Young’s modulus of the fish body are investigated. The results show that for certain body stiffness, the swimming speed and efficiency are increased with the tail-beat frequency until reaching the maximum value and then decreased. The peak speed and efficiency are also increased with the amplitude of muscle actuation. Anguilliform fish tend to vary their body stiffness to improve the swimming speed and efficiency at a high tail-beat frequency or small amplitude of muscle actuation. Furthermore, the midline motions of anguilliform fish are analyzed by the complex orthogonal decomposition (COD) method, and the discussions of fish motions associated with the variable body stiffness and the tail-beat frequency are also presented. Overall, the optimal swimming performance of anguilliform fish benefits from the matching relationships among the muscle actuation, the body stiffness, and the tail-beat frequency. Full article
(This article belongs to the Special Issue New Insights into Biological and Bioinspired Fluid Dynamics)
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21 pages, 4885 KiB  
Article
Effect of Platelet-Rich Plasma Addition on the Chemical Properties and Biological Activity of Calcium Sulfate Hemihydrate Bone Cement
by Jingyu Liu, Yifan Wang, Yanqin Liang, Shengli Zhu, Hui Jiang, Shuilin Wu, Xiang Ge and Zhaoyang Li
Biomimetics 2023, 8(2), 262; https://doi.org/10.3390/biomimetics8020262 - 15 Jun 2023
Cited by 2 | Viewed by 1781
Abstract
Currently, platelet-rich plasma (PRP) is an attractive additive for bone repair materials. PRP could enhance the osteoconductive and osteoinductive of bone cement, as well as modulate the degradation rate of calcium sulfate hemihydrate (CSH). The focus of this study was to investigate the [...] Read more.
Currently, platelet-rich plasma (PRP) is an attractive additive for bone repair materials. PRP could enhance the osteoconductive and osteoinductive of bone cement, as well as modulate the degradation rate of calcium sulfate hemihydrate (CSH). The focus of this study was to investigate the effect of different PRP ratios (P1: 20 vol%, P2: 40 vol%, and P3: 60 vol%) on the chemical properties and biological activity of bone cement. The injectability and compressive strength of the experimental group were significantly higher than those of the control. On the other hand, the addition of PRP decreased the crystal size of CSH and prolonged the degradation time. More importantly, the cell proliferation of L929 and MC3T3-E1 cells was promoted. Furthermore, qRT-PCR, alizarin red staining, and western blot analyses showed that the expressions of osteocalcin (OCN) and Runt-related transcription factor 2 (Runx2) genes and β-catenin protein were up-regulated, and mineralization of extracellular matrix was enhanced. Overall, this study provided insight into how to improve the biological activity of bone cement through PRP incorporation. Full article
(This article belongs to the Special Issue Functional Biomimetic Materials and Devices for Biomedical Applications)
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17 pages, 8426 KiB  
Article
Design, Modeling, and Control of an Aurelia-Inspired Robot Based on SMA Artificial Muscles
by Yihan Yang, Chenzhong Chu, Hu Jin, Qiqiang Hu, Min Xu and Erbao Dong
Biomimetics 2023, 8(2), 261; https://doi.org/10.3390/biomimetics8020261 - 15 Jun 2023
Cited by 3 | Viewed by 2183
Abstract
This paper presented a flexible and easily fabricated untethered underwater robot inspired by Aurelia, which is named “Au-robot”. The Au-robot is actuated by six radial fins made of shape memory alloy (SMA) artificial muscle modules, which can realize pulse jet propulsion motion. The [...] Read more.
This paper presented a flexible and easily fabricated untethered underwater robot inspired by Aurelia, which is named “Au-robot”. The Au-robot is actuated by six radial fins made of shape memory alloy (SMA) artificial muscle modules, which can realize pulse jet propulsion motion. The thrust model of the Au-robot’s underwater motion is developed and analyzed. To achieve a multimodal and smooth swimming transition for the Au-robot, a control method integrating a central pattern generator (CPG) and an adaptive regulation (AR) heating strategy is provided. The experimental results demonstrate that the Au-robot, with good bionic properties in structure and movement mode, can achieve a smooth transition from low-frequency swimming to high-frequency swimming with an average maximum instantaneous velocity of 12.61 cm/s. It shows that a robot designed and fabricated with artificial muscle can imitate biological structures and movement traits more realistically and has better motor performance. Full article
(This article belongs to the Special Issue Bio-Inspired Underwater Robot)
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17 pages, 3951 KiB  
Review
Harnessing Biofabrication Strategies to Re-Surface Osteochondral Defects: Repair, Enhance, and Regenerate
by Fabiano Bini, Salvatore D’Alessandro, Andrada Pica, Franco Marinozzi and Gianluca Cidonio
Biomimetics 2023, 8(2), 260; https://doi.org/10.3390/biomimetics8020260 - 15 Jun 2023
Cited by 3 | Viewed by 1746
Abstract
Osteochondral tissue (OC) is a complex and multiphasic system comprising cartilage and subchondral bone. The discrete OC architecture is layered with specific zones characterized by different compositions, morphology, collagen orientation, and chondrocyte phenotypes. To date, the treatment of osteochondral defects (OCD) remains a [...] Read more.
Osteochondral tissue (OC) is a complex and multiphasic system comprising cartilage and subchondral bone. The discrete OC architecture is layered with specific zones characterized by different compositions, morphology, collagen orientation, and chondrocyte phenotypes. To date, the treatment of osteochondral defects (OCD) remains a major clinical challenge due to the low self-regenerative capacity of damaged skeletal tissue, as well as the critical lack of functional tissue substitutes. Current clinical approaches fail to fully regenerate damaged OC recapitulating the zonal structure while granting long-term stability. Thus, the development of new biomimetic treatment strategies for the functional repair of OCDs is urgently needed. Here, we review recent developments in the preclinical investigation of novel functional approaches for the resurfacing of skeletal defects. The most recent studies on preclinical augmentation of OCDs and highlights on novel studies for the in vivo replacement of diseased cartilage are presented. Full article
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22 pages, 55787 KiB  
Review
The Developments of Surface-Functionalized Selenium Nanoparticles and Their Applications in Brain Diseases Therapy
by Rong Hu, Xiao Wang, Lu Han and Xiong Lu
Biomimetics 2023, 8(2), 259; https://doi.org/10.3390/biomimetics8020259 - 15 Jun 2023
Cited by 7 | Viewed by 2404
Abstract
Selenium (Se) and its organic and inorganic compounds in dietary supplements have been found to possess excellent pharmacodynamics and biological responses. However, Se in bulk form generally exhibits low bioavailability and high toxicity. To address these concerns, nanoscale selenium (SeNPs) with different forms, [...] Read more.
Selenium (Se) and its organic and inorganic compounds in dietary supplements have been found to possess excellent pharmacodynamics and biological responses. However, Se in bulk form generally exhibits low bioavailability and high toxicity. To address these concerns, nanoscale selenium (SeNPs) with different forms, such as nanowires, nanorods, and nanotubes, have been synthesized, which have become increasingly popular in biomedical applications owing to their high bioavailability and bioactivity, and are widely used in oxidative stress-induced cancers, diabetes, and other diseases. However, pure SeNPs still encounter problems when applied in disease therapy because of their poor stability. The surface functionalization strategy has become increasingly popular as it sheds light to overcome these limitations in biomedical applications and further improve the biological activity of SeNPs. This review summarizes synthesis methods and surface functionalization strategies employed for the preparation of SeNPs and highlights their applications in treating brain diseases. Full article
(This article belongs to the Special Issue Functional Biomimetic Materials and Devices for Biomedical Applications)
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15 pages, 6185 KiB  
Article
Research on Walking Gait Planning and Simulation of a Novel Hybrid Biped Robot
by Peng Sun, Yunfei Gu, Haoyu Mao, Zhao Chen and Yanbiao Li
Biomimetics 2023, 8(2), 258; https://doi.org/10.3390/biomimetics8020258 - 15 Jun 2023
Cited by 7 | Viewed by 1920
Abstract
A kinematics analysis of a new hybrid mechanical leg suitable for bipedal robots was carried out and the gait of the robot walking on flat ground was planned. Firstly, the kinematics of the hybrid mechanical leg were analyzed and the applicable relevant models [...] Read more.
A kinematics analysis of a new hybrid mechanical leg suitable for bipedal robots was carried out and the gait of the robot walking on flat ground was planned. Firstly, the kinematics of the hybrid mechanical leg were analyzed and the applicable relevant models were established. Secondly, based on the preliminary motion requirements, the inverted pendulum model was used to divide the robot walking into three stages for gait planning: mid-step, start and stop. In the three stages of robot walking, the forward and lateral robot centroid motion trajectories and the swinging leg joint trajectories were calculated. Finally, dynamic simulation software was used to simulate the virtual prototype of the robot, achieving its stable walking on flat ground in the virtual environment, and verifying the feasibility of the mechanism design and gait planning. This study provides a reference for the gait planning of hybrid mechanical legged bipedal robots and lays the foundation for further research on the robots involved in this thesis. Full article
(This article belongs to the Special Issue Design and Control of a Bio-Inspired Robot)
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24 pages, 29082 KiB  
Article
Three-Dimensional Printing of Living Mycelium-Based Composites: Material Compositions, Workflows, and Ways to Mitigate Contamination
by Alale Mohseni, Fabricio Rocha Vieira, John A. Pecchia and Benay Gürsoy
Biomimetics 2023, 8(2), 257; https://doi.org/10.3390/biomimetics8020257 - 14 Jun 2023
Cited by 14 | Viewed by 8332
Abstract
The construction industry makes a significant contribution to global CO2 emissions. Material extraction, processing, and demolition account for most of its environmental impact. As a response, there is an increasing interest in developing and implementing innovative biomaterials that support a circular economy, [...] Read more.
The construction industry makes a significant contribution to global CO2 emissions. Material extraction, processing, and demolition account for most of its environmental impact. As a response, there is an increasing interest in developing and implementing innovative biomaterials that support a circular economy, such as mycelium-based composites. The mycelium is the network of hyphae of fungi. Mycelium-based composites are renewable and biodegradable biomaterials obtained by ceasing mycelial growth on organic substrates, including agricultural waste. Cultivating mycelium-based composites within molds, however, is often wasteful, especially if molds are not reusable or recyclable. Shaping mycelium-based composites using 3D printing can minimize mold waste while allowing intricate forms to be fabricated. In this research, we explore the use of waste cardboard as a substrate for cultivating mycelium-based composites and the development of extrudable mixtures and workflows for 3D-printing mycelium-based components. In this paper, existing research on the use of mycelium-based material in recent 3D printing efforts was reviewed. This review is followed by the MycoPrint experiments that we conducted, and we focus on the main challenges that we faced (i.e., contamination) and the ways in which we addressed them. The results of this research demonstrate the feasibility of using waste cardboard as a substrate for cultivating mycelia and the potential for developing extrudable mixtures and workflows for 3D-printing mycelium-based components. Full article
(This article belongs to the Special Issue Biomimicry and 3D Printing of Living Materials)
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15 pages, 2091 KiB  
Article
Design and Simulation of On-Orbit Assembly System Based on Insect-Inspired Transportation
by Yuetian Shi, Xuyan Hou, Guowei Gao, Zhonglai Na, Yuhui Liu and Zongquan Deng
Biomimetics 2023, 8(2), 256; https://doi.org/10.3390/biomimetics8020256 - 14 Jun 2023
Cited by 3 | Viewed by 1721
Abstract
In response to the requirements of large-scale space in-orbit assembly and the special environment of low gravity in space, this paper proposes a small robot structure with the integration of assembly, connection, and vibration reduction functionalities. Each robot consists of a body and [...] Read more.
In response to the requirements of large-scale space in-orbit assembly and the special environment of low gravity in space, this paper proposes a small robot structure with the integration of assembly, connection, and vibration reduction functionalities. Each robot consists of a body and three composite mechanical arms-legs, which can dock and transfer assembly units with the transport spacecraft unit, and also crawl along the edge truss of the assembly unit to a designated location to complete in-orbit assembly while ensuring precision. A theoretical model of robot motion was established for simulation studies, and in the research process, the vibration of the assembly unit was studied, and preliminary adjustments were made to address the vibration issue. The results show that this structure is feasible for in-orbit assembly schemes and has good adjustment ability for flexible vibration. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Space Applications)
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33 pages, 14420 KiB  
Article
A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network
by Karla Avilés-Mendoza, Neil George Gaibor-León, Víctor Asanza, Leandro L. Lorente-Leyva and Diego H. Peluffo-Ordóñez
Biomimetics 2023, 8(2), 255; https://doi.org/10.3390/biomimetics8020255 - 14 Jun 2023
Cited by 2 | Viewed by 3993
Abstract
About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, [...] Read more.
About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15. Full article
(This article belongs to the Special Issue Bionic Artificial Neural Networks and Artificial Intelligence)
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25 pages, 8035 KiB  
Article
A Study on Site Selection for Regional Air Rescue Centers Based on Multi-Objective Jellyfish Search Algorithm
by Yong Liao, Yiyang Zhao, Na Fang and Jie Huang
Biomimetics 2023, 8(2), 254; https://doi.org/10.3390/biomimetics8020254 - 14 Jun 2023
Viewed by 1512
Abstract
In recent years, air emergency rescue capabilities have become increasingly important as an indicator of national comprehensive strength and development status. Air emergency rescue performs an indispensable role in addressing social emergencies by virtue of its fast response capabilities and extensive coverage. This [...] Read more.
In recent years, air emergency rescue capabilities have become increasingly important as an indicator of national comprehensive strength and development status. Air emergency rescue performs an indispensable role in addressing social emergencies by virtue of its fast response capabilities and extensive coverage. This vital aspect of emergency response ensures the timely deployment of rescue personnel and resources, enabling efficient operations in diverse and often challenging environments. To enhance regional emergency response capabilities, this paper presents a novel siting model that overcomes the limitation of single-objective approaches by integrating multiple objectives and considering the synergistic effects of network nodes, and the corresponding efficient solving algorithm is designed for this model. First, a multi-objective optimization function is established that fully incorporates the construction cost of the rescue station, response time, and radiation range. A radiation function is developed to evaluate the degree of radiation for each candidate airport. Second, the multi-objective jellyfish search algorithm (MOJS) is employed to search for Pareto optimal solutions of the model using MATLAB tools. Finally, the proposed algorithm is applied to analyze and verify the site selection for a regional air emergency rescue center in a certain region of China, and ArcGIS tools are used to draw the site selection results separately by prioritizing the construction cost under different numbers of site selection points. The results demonstrate that the proposed model can achieve the desired site selection goals, thus providing a feasible and accurate method for future air emergency rescue station selection problems. Full article
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19 pages, 11505 KiB  
Article
Research and Experiment on a Bionic Fish Based on High-Frequency Vibration Characteristics
by Bo Zhang, Yu Chen, Zhuo Wang and Hongwen Ma
Biomimetics 2023, 8(2), 253; https://doi.org/10.3390/biomimetics8020253 - 14 Jun 2023
Cited by 1 | Viewed by 2205
Abstract
This paper takes the high-frequency vibration characteristics of a bionic robot fish as the research object. Through research on the vibration characteristics of a bionic fish, we quantified the role of voltage and beat frequency in high-speed and stable swimming. We proposed a [...] Read more.
This paper takes the high-frequency vibration characteristics of a bionic robot fish as the research object. Through research on the vibration characteristics of a bionic fish, we quantified the role of voltage and beat frequency in high-speed and stable swimming. We proposed a new type of electromagnetic drive. The tail is made of 0° silica gel to simulate the elastic characteristics of fish muscles. We completed a series of experimental studies on the vibration characteristics of biomimetic robotic fish. Through the single-joint fishtail underwater experiment, the influence of vibration characteristics on parameters during swimming was discussed. In terms of control, the central mode generator control method (CPG) control model is adopted, and a replacement layer is designed in combination with particle swarm optimization (PSO). By changing the elastic modulus of the fishtail, the fishtail resonates with the vibrator, and the swimming efficiency of the bionic fish is improved. Finally, through the prototype experiment, it is found that the bionic robot fish can achieve high-speed swimming through high-frequency vibration. Full article
(This article belongs to the Special Issue Bionic Robotic Fish)
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13 pages, 2912 KiB  
Article
Using the MNL Model in a Mobile Device’s Indoor Positioning
by Feng Xie, Ming Xie and Cheng Wang
Biomimetics 2023, 8(2), 252; https://doi.org/10.3390/biomimetics8020252 - 13 Jun 2023
Viewed by 1662
Abstract
Indoor Positioning Services (IPS) allow mobile devices or bionic robots to locate themselves quickly and accurately in large commercial complexes, shopping malls, supermarkets, exhibition venues, parking garages, airports, or train hubs, and access surrounding information. Wi-Fi-based indoor positioning technology can use existing WLAN [...] Read more.
Indoor Positioning Services (IPS) allow mobile devices or bionic robots to locate themselves quickly and accurately in large commercial complexes, shopping malls, supermarkets, exhibition venues, parking garages, airports, or train hubs, and access surrounding information. Wi-Fi-based indoor positioning technology can use existing WLAN networks, and has promising prospects for broad market applications. This paper presents a method using the Multinomial Logit Model (MNL) to generate Wi-Fi signal fingerprints for positioning in real time. In an experiment, 31 locations were randomly selected and tested to validate the model, showing mobile devices could determine their locations with an accuracy of around 3 m (2.53 m median). Full article
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24 pages, 9750 KiB  
Article
An Experimental and Simulation Study of the Active Camber Morphing Concept on Airfoils Using Bio-Inspired Structures
by Alexsteven Dharmdas, Arun Y. Patil, Azar Baig, Owais Z. Hosmani, Shridhar N. Mathad, Mallikarjunagouda B. Patil, Raman Kumar, Basavaraj B. Kotturshettar and Islam Md Rizwanul Fattah
Biomimetics 2023, 8(2), 251; https://doi.org/10.3390/biomimetics8020251 - 13 Jun 2023
Cited by 8 | Viewed by 3063
Abstract
Birds are capable of morphing their wings across different flight modes and speeds to improve their aerodynamic performance. In light of this, the study aims to investigate a more optimized solution compared to conventional structural wing designs. The design challenges faced by the [...] Read more.
Birds are capable of morphing their wings across different flight modes and speeds to improve their aerodynamic performance. In light of this, the study aims to investigate a more optimized solution compared to conventional structural wing designs. The design challenges faced by the aviation industry today require innovative techniques to improve flight efficiency and minimize environmental impact. This study focuses on the aeroelastic impact validation of wing trailing edge morphing, which undergoes significant structural changes to enhance performance as per mission requirements. The approach to design-concept, modeling, and construction described in this study is generalizable and requires lightweight and actively deformable structures. The objective of this work is to demonstrate the aerodynamic efficiency of an innovative structural design and trailing edge morphing concept compared to conventional wing-flap configurations. The analysis revealed that the maximum displacement at a 30-degree deflection is 47.45 mm, while the maximum stress is 21 MPa. Considering that the yield strength of ABS material is 41.14 MPa, this kerf morphing structure, with a safety factor of 2.5, can withstand both structural and aerodynamic loads. The analysis results of the flap and morph configurations showed a 27% efficiency improvement, which was confirmed through the convergence criteria in ANSYS CFX. Full article
(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics 2.0)
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14 pages, 6228 KiB  
Article
Hand Grasp Pose Prediction Based on Motion Prior Field
by Xu Shi, Weichao Guo, Wei Xu and Xinjun Sheng
Biomimetics 2023, 8(2), 250; https://doi.org/10.3390/biomimetics8020250 - 12 Jun 2023
Cited by 1 | Viewed by 2131
Abstract
Shared control of bionic robot hands has recently attracted much research attention. However, few studies have performed predictive analysis for grasp pose, which is vital for the pre-shape planning of robotic wrists and hands. Aiming at shared control of dexterous hand grasp planning, [...] Read more.
Shared control of bionic robot hands has recently attracted much research attention. However, few studies have performed predictive analysis for grasp pose, which is vital for the pre-shape planning of robotic wrists and hands. Aiming at shared control of dexterous hand grasp planning, this paper proposes a framework for grasp pose prediction based on the motion prior field. To map the hand–object pose to the final grasp pose, an object-centered motion prior field is established to learn the prediction model. The results of motion capture reconstruction show that, with the input of a 7-dimensional pose and cluster manifolds of dimension 100, the model performs best in terms of prediction accuracy (90.2%) and error distance (1.27 cm) in the sequence. The model makes correct predictions in the first 50% of the sequence during hand approach to the object. The outcomes of this study enable prediction of the grasp pose in advance as the hand approaches the object, which is very important for enabling the shared control of bionic and prosthetic hands. Full article
(This article belongs to the Special Issue Bionic Robot Hand: Dexterous Manipulation and Robust Grasping)
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28 pages, 5300 KiB  
Article
WOA-Based Robust Congestion Control Scheme with Two Kinds of Propagation Latencies and External Disturbance in Software-Defined Wireless Networks
by Xi Hu, Zhiwei Shen, Xin Xiong, Siqi Zhang, Junming Chang and Wang Gao
Biomimetics 2023, 8(2), 249; https://doi.org/10.3390/biomimetics8020249 - 10 Jun 2023
Cited by 1 | Viewed by 1579
Abstract
This paper proposes a novel WOA-based robust control scheme with two kinds of propagation latencies and external disturbance implemented in Software-Defined Wireless Networks (SDWNs) to maximize overall throughput and enhance the stability of the global network. Firstly, an adjustment model developed using the [...] Read more.
This paper proposes a novel WOA-based robust control scheme with two kinds of propagation latencies and external disturbance implemented in Software-Defined Wireless Networks (SDWNs) to maximize overall throughput and enhance the stability of the global network. Firstly, an adjustment model developed using the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme with propagation latency in device-to-device paths and a closed-loop congestion control model with propagation latency in device–controller pairs are proposed, and the effect of channel competition from neighboring forwarding devices is analyzed. Subsequently, a robust congestion control model with two kinds of propagation latencies and external disturbance is established. Then, a new WOA-based scheduling strategy that considers each individual whale as a specific scheduling plan to allocate appropriate sending rates at the source side is presented to maximize the global network throughput. Afterward, the sufficient conditions are derived using Lyapunov–Krasovskii functionals and formulated using Linear Matrix Inequalities (LMIs). Finally, a numerical simulation is conducted to verify the effectiveness of this proposed scheme. Full article
(This article belongs to the Special Issue Learning from Nature: Bionics in Design Practice)
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18 pages, 2095 KiB  
Article
Robot Programming from Fish Demonstrations
by Claudio Massimo Coppola, James Bradley Strong, Lissa O’Reilly, Sarah Dalesman and Otar Akanyeti
Biomimetics 2023, 8(2), 248; https://doi.org/10.3390/biomimetics8020248 - 10 Jun 2023
Cited by 1 | Viewed by 1617
Abstract
Fish are capable of learning complex relations found in their surroundings, and harnessing their knowledge may help to improve the autonomy and adaptability of robots. Here, we propose a novel learning from demonstration framework to generate fish-inspired robot control programs with as little [...] Read more.
Fish are capable of learning complex relations found in their surroundings, and harnessing their knowledge may help to improve the autonomy and adaptability of robots. Here, we propose a novel learning from demonstration framework to generate fish-inspired robot control programs with as little human intervention as possible. The framework consists of six core modules: (1) task demonstration, (2) fish tracking, (3) analysis of fish trajectories, (4) acquisition of robot training data, (5) generating a perception–action controller, and (6) performance evaluation. We first describe these modules and highlight the key challenges pertaining to each one. We then present an artificial neural network for automatic fish tracking. The network detected fish successfully in 85% of the frames, and in these frames, its average pose estimation error was less than 0.04 body lengths. We finally demonstrate how the framework works through a case study focusing on a cue-based navigation task. Two low-level perception–action controllers were generated through the framework. Their performance was measured using two-dimensional particle simulations and compared against two benchmark controllers, which were programmed manually by a researcher. The fish-inspired controllers had excellent performance when the robot was started from the initial conditions used in fish demonstrations (>96% success rate), outperforming the benchmark controllers by at least 3%. One of them also had an excellent generalisation performance when the robot was started from random initial conditions covering a wider range of starting positions and heading angles (>98% success rate), again outperforming the benchmark controllers by 12%. The positive results highlight the utility of the framework as a research tool to form biological hypotheses on how fish navigate in complex environments and design better robot controllers on the basis of biological findings. Full article
(This article belongs to the Special Issue Biorobotics)
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24 pages, 2306 KiB  
Article
SNS-Toolbox: An Open Source Tool for Designing Synthetic Nervous Systems and Interfacing Them with Cyber–Physical Systems
by William R. P. Nourse, Clayton Jackson, Nicholas S. Szczecinski and Roger D. Quinn
Biomimetics 2023, 8(2), 247; https://doi.org/10.3390/biomimetics8020247 - 10 Jun 2023
Cited by 2 | Viewed by 1877
Abstract
One developing approach for robotic control is the use of networks of dynamic neurons connected with conductance-based synapses, also known as Synthetic Nervous Systems (SNS). These networks are often developed using cyclic topologies and heterogeneous mixtures of spiking and non-spiking neurons, which is [...] Read more.
One developing approach for robotic control is the use of networks of dynamic neurons connected with conductance-based synapses, also known as Synthetic Nervous Systems (SNS). These networks are often developed using cyclic topologies and heterogeneous mixtures of spiking and non-spiking neurons, which is a difficult proposition for existing neural simulation software. Most solutions apply to either one of two extremes, the detailed multi-compartment neural models in small networks, and the large-scale networks of greatly simplified neural models. In this work, we present our open-source Python package SNS-Toolbox, which is capable of simulating hundreds to thousands of spiking and non-spiking neurons in real-time or faster on consumer-grade computer hardware. We describe the neural and synaptic models supported by SNS-Toolbox, and provide performance on multiple software and hardware backends, including GPUs and embedded computing platforms. We also showcase two examples using the software, one for controlling a simulated limb with muscles in the physics simulator Mujoco, and another for a mobile robot using ROS. We hope that the availability of this software will reduce the barrier to entry when designing SNS networks, and will increase the prevalence of SNS networks in the field of robotic control. Full article
(This article belongs to the Special Issue Design and Control of a Bio-Inspired Robot)
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45 pages, 10013 KiB  
Review
Biomimetic Scaffolds for Tendon Tissue Regeneration
by Lvxing Huang, Le Chen, Hengyi Chen, Manju Wang, Letian Jin, Shenghai Zhou, Lexin Gao, Ruwei Li, Quan Li, Hanchang Wang, Can Zhang and Junjuan Wang
Biomimetics 2023, 8(2), 246; https://doi.org/10.3390/biomimetics8020246 - 9 Jun 2023
Cited by 15 | Viewed by 6000
Abstract
Tendon tissue connects muscle to bone and plays crucial roles in stress transfer. Tendon injury remains a significant clinical challenge due to its complicated biological structure and poor self-healing capacity. The treatments for tendon injury have advanced significantly with the development of technology, [...] Read more.
Tendon tissue connects muscle to bone and plays crucial roles in stress transfer. Tendon injury remains a significant clinical challenge due to its complicated biological structure and poor self-healing capacity. The treatments for tendon injury have advanced significantly with the development of technology, including the use of sophisticated biomaterials, bioactive growth factors, and numerous stem cells. Among these, biomaterials that the mimic extracellular matrix (ECM) of tendon tissue would provide a resembling microenvironment to improve efficacy in tendon repair and regeneration. In this review, we will begin with a description of the constituents and structural features of tendon tissue, followed by a focus on the available biomimetic scaffolds of natural or synthetic origin for tendon tissue engineering. Finally, we will discuss novel strategies and present challenges in tendon regeneration and repair. Full article
(This article belongs to the Special Issue Biomimetic Platform for Tissue Regeneration 2.0)
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33 pages, 7141 KiB  
Review
Molecularly Imprinted Polymer-Based Biomimetic Systems for Sensing Environmental Contaminants, Biomarkers, and Bioimaging Applications
by Kalaipriya Ramajayam, Selvaganapathy Ganesan, Purnimajayasree Ramesh, Maya Beena, Thangavelu Kokulnathan and Arunkumar Palaniappan
Biomimetics 2023, 8(2), 245; https://doi.org/10.3390/biomimetics8020245 - 8 Jun 2023
Cited by 18 | Viewed by 3362
Abstract
Molecularly imprinted polymers (MIPs), a biomimetic artificial receptor system inspired by the human body’s antibody-antigen reactions, have gained significant attraction in the area of sensor development applications, especially in the areas of medical, pharmaceutical, food quality control, and the environment. MIPs are found [...] Read more.
Molecularly imprinted polymers (MIPs), a biomimetic artificial receptor system inspired by the human body’s antibody-antigen reactions, have gained significant attraction in the area of sensor development applications, especially in the areas of medical, pharmaceutical, food quality control, and the environment. MIPs are found to enhance the sensitivity and specificity of typical optical and electrochemical sensors severalfold with their precise binding to the analytes of choice. In this review, different polymerization chemistries, strategies used in the synthesis of MIPs, and various factors influencing the imprinting parameters to achieve high-performing MIPs are explained in depth. This review also highlights the recent developments in the field, such as MIP-based nanocomposites through nanoscale imprinting, MIP-based thin layers through surface imprinting, and other latest advancements in the sensor field. Furthermore, the role of MIPs in enhancing the sensitivity and specificity of sensors, especially optical and electrochemical sensors, is elaborated. In the later part of the review, applications of MIP-based optical and electrochemical sensors for the detection of biomarkers, enzymes, bacteria, viruses, and various emerging micropollutants like pharmaceutical drugs, pesticides, and heavy metal ions are discussed in detail. Finally, MIP’s role in bioimaging applications is elucidated with a critical assessment of the future research directions for MIP-based biomimetic systems. Full article
(This article belongs to the Special Issue Molecularly Imprinted Systems for Biorecognition and Biosensing)
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11 pages, 1995 KiB  
Article
Finger Kinematics during Human Hand Grip and Release
by Xiaodong Li, Rongwei Wen, Dehao Duanmu, Wei Huang, Kinto Wan and Yong Hu
Biomimetics 2023, 8(2), 244; https://doi.org/10.3390/biomimetics8020244 - 8 Jun 2023
Cited by 4 | Viewed by 2924
Abstract
A bionic robotic hand can perform many movements similar to a human hand. However, there is still a significant gap in manipulation between robot and human hands. It is necessary to understand the finger kinematics and motion patterns of human hands to improve [...] Read more.
A bionic robotic hand can perform many movements similar to a human hand. However, there is still a significant gap in manipulation between robot and human hands. It is necessary to understand the finger kinematics and motion patterns of human hands to improve the performance of robotic hands. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hands of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a larger dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Additionally, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by the PIP joint. Regarding the finger sequence, the thumb started to move before the four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided a kinematic reference for the design of robotic hands and thus contributes to its development. Full article
(This article belongs to the Special Issue Bionic Robot Hand: Dexterous Manipulation and Robust Grasping)
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25 pages, 4175 KiB  
Article
Vibration State Identification of Hydraulic Units Based on Improved Artificial Rabbits Optimization Algorithm
by Qingjiao Cao, Liying Wang, Weiguo Zhao, Zhouxiang Yuan, Anran Liu, Yanfeng Gao and Runfeng Ye
Biomimetics 2023, 8(2), 243; https://doi.org/10.3390/biomimetics8020243 - 8 Jun 2023
Cited by 6 | Viewed by 1565
Abstract
To improve the identification accuracy of the vibration states of hydraulic units, an improved artificial rabbits optimization algorithm (IARO) adopting an adaptive weight adjustment strategy is developed for optimizing the support vector machine (SVM) to obtain an identification model, and the vibration signals [...] Read more.
To improve the identification accuracy of the vibration states of hydraulic units, an improved artificial rabbits optimization algorithm (IARO) adopting an adaptive weight adjustment strategy is developed for optimizing the support vector machine (SVM) to obtain an identification model, and the vibration signals with different states are classified and identified. The variational mode decomposition (VMD) method is used to decompose the vibration signals, and the multi-dimensional time-domain feature vectors of the signals are extracted. The IARO algorithm is used to optimize the parameters of the SVM multi-classifier. The multi-dimensional time-domain feature vectors are input into the IARO-SVM model to realize the classification and identification of vibration signal states, and the results are compared with those of the ARO-SVM model, ASO-SVM model, PSO-SVM model and WOA-SVM model. The comparative results show that the average identification accuracy of the IARO-SVM model is higher at 97.78% than its competitors, which is 3.34% higher than the closest ARO-SVM model. Therefore, the IARO-SVM model has higher identification accuracy and better stability, and can accurately identify the vibration states of hydraulic units. The research can provide a theoretical basis for the vibration identification of hydraulic units. Full article
(This article belongs to the Special Issue Nature-Inspired Computer Algorithms)
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27 pages, 3419 KiB  
Article
Improved Environmental Stimulus and Biological Competition Tactics Interactive Artificial Ecological Optimization Algorithm for Clustering
by Wenyan Guo, Mingfei Wu, Fang Dai and Yufan Qiang
Biomimetics 2023, 8(2), 242; https://doi.org/10.3390/biomimetics8020242 - 7 Jun 2023
Cited by 1 | Viewed by 1265
Abstract
An interactive artificial ecological optimization algorithm (SIAEO) based on environmental stimulus and a competition mechanism was devised to find the solution to a complex calculation, which can often become bogged down in local optimum because of the sequential execution of consumption and decomposition [...] Read more.
An interactive artificial ecological optimization algorithm (SIAEO) based on environmental stimulus and a competition mechanism was devised to find the solution to a complex calculation, which can often become bogged down in local optimum because of the sequential execution of consumption and decomposition stages in the artificial ecological optimization algorithm. Firstly, the environmental stimulus defined by population diversity makes the population interactively execute the consumption operator and decomposition operator to abate the inhomogeneity of the algorithm. Secondly, the three different types of predation modes in the consumption stage were regarded as three different tasks, and the task execution mode was determined by the maximum cumulative success rate of each individual task execution. Furthermore, the biological competition operator is recommended to modify the regeneration strategy so that the SIAEO algorithm can provide consideration to the exploitation in the exploration stage, break the equal probability execution mode of the AEO, and promote the competition among operators. Finally, the stochastic mean suppression alternation exploitation problem is introduced in the later exploitation process of the algorithm, which can tremendously heighten the SIAEO algorithm to run away the local optimum. A comparison between SIAEO and other improved algorithms is performed on the CEC2017 and CEC2019 test set. Full article
(This article belongs to the Special Issue Nature-Inspired Computer Algorithms)
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23 pages, 895 KiB  
Article
Improved Dipper-Throated Optimization for Forecasting Metamaterial Design Bandwidth for Engineering Applications
by Amal H. Alharbi, Abdelaziz A. Abdelhamid, Abdelhameed Ibrahim, S. K. Towfek, Nima Khodadadi, Laith Abualigah, Doaa Sami Khafaga and Ayman EM Ahmed
Biomimetics 2023, 8(2), 241; https://doi.org/10.3390/biomimetics8020241 - 7 Jun 2023
Cited by 21 | Viewed by 1653
Abstract
Metamaterials have unique physical properties. They are made of several elements and are structured in repeating patterns at a smaller wavelength than the phenomena they affect. Metamaterials’ exact structure, geometry, size, orientation, and arrangement allow them to manipulate electromagnetic waves by blocking, absorbing, [...] Read more.
Metamaterials have unique physical properties. They are made of several elements and are structured in repeating patterns at a smaller wavelength than the phenomena they affect. Metamaterials’ exact structure, geometry, size, orientation, and arrangement allow them to manipulate electromagnetic waves by blocking, absorbing, amplifying, or bending them to achieve benefits not possible with ordinary materials. Microwave invisibility cloaks, invisible submarines, revolutionary electronics, microwave components, filters, and antennas with a negative refractive index utilize metamaterials. This paper proposed an improved dipper throated-based ant colony optimization (DTACO) algorithm for forecasting the bandwidth of the metamaterial antenna. The first scenario in the tests covered the feature selection capabilities of the proposed binary DTACO algorithm for the dataset that was being evaluated, and the second scenario illustrated the algorithm’s regression skills. Both scenarios are part of the studies. The state-of-the-art algorithms of DTO, ACO, particle swarm optimization (PSO), grey wolf optimizer (GWO), and whale optimization (WOA) were explored and compared to the DTACO algorithm. The basic multilayer perceptron (MLP) regressor model, the support vector regression (SVR) model, and the random forest (RF) regressor model were contrasted with the optimal ensemble DTACO-based model that was proposed. In order to assess the consistency of the DTACO-based model that was developed, the statistical research made use of Wilcoxon’s rank-sum and ANOVA tests. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)
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17 pages, 4011 KiB  
Article
The Task Decomposition and Dedicated Reward-System-Based Reinforcement Learning Algorithm for Pick-and-Place
by Byeongjun Kim, Gunam Kwon, Chaneun Park and Nam Kyu Kwon
Biomimetics 2023, 8(2), 240; https://doi.org/10.3390/biomimetics8020240 - 6 Jun 2023
Cited by 3 | Viewed by 2606
Abstract
This paper proposes a task decomposition and dedicated reward-system-based reinforcement learning algorithm for the Pick-and-Place task, which is one of the high-level tasks of robot manipulators. The proposed method decomposes the Pick-and-Place task into three subtasks: two reaching tasks and one grasping task. [...] Read more.
This paper proposes a task decomposition and dedicated reward-system-based reinforcement learning algorithm for the Pick-and-Place task, which is one of the high-level tasks of robot manipulators. The proposed method decomposes the Pick-and-Place task into three subtasks: two reaching tasks and one grasping task. One of the two reaching tasks is approaching the object, and the other is reaching the place position. These two reaching tasks are carried out using each optimal policy of the agents which are trained using Soft Actor-Critic (SAC). Different from the two reaching tasks, the grasping is implemented via simple logic which is easily designable but may result in improper gripping. To assist the grasping task properly, a dedicated reward system for approaching the object is designed through using individual axis-based weights. To verify the validity of the proposed method, wecarry out various experiments in the MuJoCo physics engine with the Robosuite framework. According to the simulation results of four trials, the robot manipulator picked up and released the object in the goal position with an average success rate of 93.2%. Full article
(This article belongs to the Special Issue Artificial Intelligence for Autonomous Robots 2023)
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35 pages, 12661 KiB  
Article
Drawer Algorithm: A New Metaheuristic Approach for Solving Optimization Problems in Engineering
by Eva Trojovská, Mohammad Dehghani and Víctor Leiva
Biomimetics 2023, 8(2), 239; https://doi.org/10.3390/biomimetics8020239 - 6 Jun 2023
Cited by 23 | Viewed by 2917
Abstract
Metaheuristic optimization algorithms play an essential role in optimizing problems. In this article, a new metaheuristic approach called the drawer algorithm (DA) is developed to provide quasi-optimal solutions to optimization problems. The main inspiration for the DA is to simulate the selection of [...] Read more.
Metaheuristic optimization algorithms play an essential role in optimizing problems. In this article, a new metaheuristic approach called the drawer algorithm (DA) is developed to provide quasi-optimal solutions to optimization problems. The main inspiration for the DA is to simulate the selection of objects from different drawers to create an optimal combination. The optimization process involves a dresser with a given number of drawers, where similar items are placed in each drawer. The optimization is based on selecting suitable items, discarding unsuitable ones from different drawers, and assembling them into an appropriate combination. The DA is described, and its mathematical modeling is presented. The performance of the DA in optimization is tested by solving fifty-two objective functions of various unimodal and multimodal types and the CEC 2017 test suite. The results of the DA are compared to the performance of twelve well-known algorithms. The simulation results demonstrate that the DA, with a proper balance between exploration and exploitation, produces suitable solutions. Furthermore, comparing the performance of optimization algorithms shows that the DA is an effective approach for solving optimization problems and is much more competitive than the twelve algorithms against which it was compared to. Additionally, the implementation of the DA on twenty-two constrained problems from the CEC 2011 test suite demonstrates its high efficiency in handling optimization problems in real-world applications. Full article
(This article belongs to the Special Issue Bioinspired Algorithms)
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13 pages, 426 KiB  
Article
Solving the Min-Max Clustered Traveling Salesmen Problem Based on Genetic Algorithm
by Xiaoguang Bao, Guojun Wang, Lei Xu and Zhaocai Wang
Biomimetics 2023, 8(2), 238; https://doi.org/10.3390/biomimetics8020238 - 6 Jun 2023
Cited by 7 | Viewed by 1846
Abstract
The min-max clustered traveling salesmen problem (MMCTSP) is a generalized variant of the classical traveling salesman problem (TSP). In this problem, the vertices of the graph are partitioned into a given number of clusters and we are asked to find a collection of [...] Read more.
The min-max clustered traveling salesmen problem (MMCTSP) is a generalized variant of the classical traveling salesman problem (TSP). In this problem, the vertices of the graph are partitioned into a given number of clusters and we are asked to find a collection of tours to visit all the vertices with the constraint that the vertices of each cluster are visited consecutively. The objective of the problem is to minimize the weight of the maximum weight tour. For this problem, a two-stage solution method based on a genetic algorithm is designed according to the problem characteristics. The first stage is to determine the visiting order of the vertices within each cluster, by abstracting a TSP from the corresponding cluster and applying a genetic algorithm to solve it. The second stage is to determine the assignment of clusters to salesmen and the visiting order of the assigned clusters. In this stage, by representing each cluster as a node and using the result of the first stage and the ideas of greed and random, we define the distances between each two nodes and construct a multiple traveling salesmen problem (MTSP), and then apply a grouping-based genetic algorithm to solve it. Computational experiments indicate that the proposed algorithm can obtain better solution results for various scale instances and shows good solution performance. Full article
(This article belongs to the Special Issue Nature-Inspired Computer Algorithms)
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