One of the main problems in controlling the shape of active structures （AS） is to determine the actuations that drive the structure from the current state to the target state. Model-based methods such as stochastic ...One of the main problems in controlling the shape of active structures （AS） is to determine the actuations that drive the structure from the current state to the target state. Model-based methods such as stochastic search require a known type of load and relatively long computational time, which limits the practical use of AS in civil engineering. Moreover, additive errors may be produced because of the discrepancy between analytic models and real structures. To overcome these limitations, this paper presents a compound system called WAS, which combines AS with a wireless sensor and actuator network （WSAN）. A bio-inspired control framework imitating the activity of the nervous systems of animals is proposed for WAS. A typical example is tested for verification. In the example, a triangular tensegrity prism that aims to maintain its original height is integrated with a WSAN that consists of a central controller, three actuators, and three sensors. The result demonstrates the feasibility of the proposed concept and control framework in cases of unknown loads that include different types, distributions, magnitudes, and directions. The proposed control framework can also act as a supplementary means to improve the efficiency and accuracy of control frameworks based on a common stochastic search.展开更多
Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary...Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary Soft Tri-Legged Robot(STLR)that improves movement and obstacle-avoidance skills by using a bio-inspired pneumatic artificial muscle(Bubble Artificial Muscles)and a bio-inspired tactile sensor(TacTip).The STLR is activated by BAMs,which are flexible,pneu-matic-driven actuators that provide fine control over forward,backward,and steering movements.Obstacle identification and avoidance are facilitated by the TacTip sensor,which delivers tactile input for traversing unstructured terrains.We delineate the mechanical features of the BAMs,assess the functionality of the robot's legs,and elaborate on the incorpora-tion of the tactile sensing system.Experimental results demonstrate that the STLR can effectively achieve multi-directional flexible movement and obstacle avoidance through a cross-modal perception-actuation mechanism.This study highlights the promise of soft robotics for search and rescue,medical aid,and autonomous exploration,while delineating difficulties and opportunities for future improvements in functionality and efficiency.展开更多
Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined ...Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.展开更多
Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track pred...Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.展开更多
Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this...Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this review,we systematically survey the basics of MHMRs,from propulsion mechanism,magnetization and control methods to biomedical applications,aiming to provide readers with an easily understandable overview and fundamental knowledge on implementing MHMRs.The MHMRs are actuated by rotating magnetic fields,achieving steering and rotation through magnetic torque,and converting rotation into forward motion through the helical structure.Magnetization methods for MHMRs are reviewed into three types:attaching magnets,magnetic coatings,and magnetic powder doping.Additionally,this review discusses the control methods for MHMRs,covering imaging techniques,path tracking control—including classical control algorithms and increasingly popular learning-based methods,and swarm control.Subsequently,a comprehensive survey is conducted on the biomedical applications of MHMRs in the treatment of vascular diseases,drug delivery,cell delivery,and their integration with catheters.We finally provide a perspective about future challenges in MHMR research,including enhancing functional design capabilities,developing swarm-assisted independent control mechanisms,refining in vivo imaging techniques,and ensuring robust biocompatibility for safe medical use.展开更多
Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustnes...Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.展开更多
This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task...This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task allocation for vigilance roles and the coverage planning of the perception ranges.Firstly,vigilance behavioral patterns and processes in animal populations within natural habitats are investigated.Inspired by these biological vigilance behaviors,an efficient vigilance task allocation model for MAS is proposed.Secondly,the subsequent optimization of task layouts can achieve efficient surveillance coverage with fewer agents,minimizing resource consumption.Thirdly,an improved particle swarm optimization(IPSO)algorithm is proposed,which incorporates fitness-driven adaptive inertia weight dynamics.According to simulation analysis and comparative studies,optimal parameter configurations for genetic algorithm(GA)and IPSO are determined.Finally,the results indicate the proposed IPSO's superior performance to both GA and standard particle swarm optimization(PSO)in vigilance task allocation optimization,with satisfying advantages in computational efficiency and solution quality.展开更多
The formation control problem for underactuated unmanned surface vehicles(USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by exter...The formation control problem for underactuated unmanned surface vehicles(USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law,and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller.展开更多
A bio-inspired global finite time control using global fast-terminal sliding mode controller and radial basis function network is presented in this article,to address the attitude tracking control problem of the three...A bio-inspired global finite time control using global fast-terminal sliding mode controller and radial basis function network is presented in this article,to address the attitude tracking control problem of the three degree-of-freedom four-rotor hover system.The proposed controller provides convergence of system states in a predetermined finite time and estimates the unmodeled dynamics of the four-rotor system.Dynamic model of the four-rotor system is derived with Newton’s force equations.The unknown dynamics of four-rotor systems are estimated using Radial basis function.The bio-inspired global fast terminal sliding mode controller is proposed to provide chattering free finite time error convergence and to provide optimal tracking of the attitude angles while being subjected to unknown dynamics.The global stability proof of the designed controller is provided on the basis of Lyapunov stability theorem.The proposed controller is validated by(i)conducting an experiment through implementing it on the laboratory-based hover system,and(ii)through simulations.Performance of the proposed control scheme is also compared with classical and intelligent controllers.The performance comparison exhibits that the designed controller has quick transient response and improved chattering free steady state performance.The proposed bioinspired global fast terminal sliding mode controller offers improved estimation and better tracking performance than the traditional controllers.In addition,the proposed controller is computationally cost effective and can be implanted on multirotor unmanned air vehicles with limited computational processing capabilities.展开更多
Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering applications.The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System A...Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering applications.The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System Algorithm(ACSA).The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this process.The work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions,identified as classical benchmark functions.The method was subsequently examined by application to 12 CEC 2022 benchmark problems of different complexities.Furthermore,the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches,including evolutionary,human,physics,and swarm-based.Subsequently,a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing literature.The results show that the ACSA strategy can quickly reach the global optimum,avoid getting trapped in local optima,and effectively maintain a balance between exploration and exploitation.ACSA outperformed 42 algorithms statistically,according to post-hoc tests.It also outperformed 9 algorithms quantitatively.The study concludes that ACSA offers competitive solutions in comparison to popüler methods.展开更多
There is an urgent need for the application of broadband Microwave Absorption(MA)structures on the leading edges of aircraft wings,which requires the MA structures to possess both the broadband MA performance and grea...There is an urgent need for the application of broadband Microwave Absorption(MA)structures on the leading edges of aircraft wings,which requires the MA structures to possess both the broadband MA performance and great surface conformability.To meet these requirements,we designed and fabricated a flexible bioinspired meta-structure with ultra-broadband MA,thin thickness and excellent surface conformality.The carbonyl iron powder-carbon nanotubes-polydimethylsiloxane composite was synthesized by physical blending method for fabricating the MA meta-structure.Through geometry-electromagnetic optimal design by heuristic optimization algorithm,the meta-structure mimicking to the nipple photonic nanostructures on the eyes of moth can achieve ultra-broadband MA performance of 35.14 GHz MA bandwidth(reflection loss≤–10 dB),covering 4.86–40.00 GHz,with thickness of only 4.3 mm.Through simple fabrication processes,the meta-structure has been successfully fabricated and bonded on wings’leading edges,exhibiting excellent surface conformability.Furthermore,the designed flexible MA meta-structure possesses significant Radar Cross-Section(RCS)reduction capability,as demonstrated by the RCS analysis of an unmanned aerial vehicle.This flexible ultra-broadband MA meta-structure provides an outstanding candidate to meet the radar stealth requirement of variable curvature structures on aircraft.展开更多
The development of a tailless Flapping Wing Micro Aerial Vehicle(FWMAV)inspired by the hummingbird is presented in this work.By implementing mechanical simplifications,it is possible to use planar machining technology...The development of a tailless Flapping Wing Micro Aerial Vehicle(FWMAV)inspired by the hummingbird is presented in this work.By implementing mechanical simplifications,it is possible to use planar machining technology for manufacturing of the FWMAV’s body,greatly reducing assembly errors.Traditionally,studies on flapping wing aircraft are limited to open-loop wing kinematics control.In this work,an instantaneous closed-loop wing trajectory tracking control system is introduced to minimize wings’trajectory tracking errors.The control system is based on Field-Oriented Control(FOC)with a loop shaping compensation technique near the flapping frequency.Through frequency analysis,the loop shaping compensator ensures the satisfactory bandwidth and performance for the closed-loop flapping system.To implement the proposed controller,a compact autopilot board integrated with FOC hardware is designed,weighing only 2.5 g.By utilizing precise wing trajectory tracking control,the hummingbird-inspired FWMAV demonstrates superior ability to resist external disturbances and exhibits reduced attitude tracking errors during hovering flight compared to the open-loop wing motion.展开更多
McKibben muscles are increasingly used in many robotic applications due to their advantages of lightweight,compliant,and skeletal muscles-like behaviours.However,there are still huge challenges in the motion control o...McKibben muscles are increasingly used in many robotic applications due to their advantages of lightweight,compliant,and skeletal muscles-like behaviours.However,there are still huge challenges in the motion control of McKibben muscles due to the system nonlinearity(e.g.,hysteresis)and model uncertainties.To investigate the control issues,a soft artificial arm actuated by an antagonistic pair of McKibben muscles,mimicking the biological structure of skeleton-muscle systems,is developed.Inspired by the biological motor control capability that humans can control and coordinate a group of muscles to achieve complex motions,a cerebellum-like controller based on Spiking Neural Networks(SNNs)is employed for the motion control of the developed artificial arm.Benefit from the employment of the SNN-based cerebellar model,the proposed control scheme provides online adaptive learning capability,good computational efficiency,fast response,and strong robustness.Finally,several simulations and experiments are conducted subject to different environmental disturbances.Both simulation and experimental results verify that the proposed method can achieve good tracking performance,adaptability,and strong robustness.展开更多
To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subj...To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subjected to Gaussian white noise and galloping excitation,simulating the flapping pattern of a seagull and its interaction with wind force.The equivalent linearization method is utilized to convert the original nonlinear model into the Itôstochastic differential equation by minimizing the mean squared error.Then,the second-order steady-state moments about the displacement,velocity,and voltage are derived by combining the moment analysis theory.The theoretical results are simulated numerically to analyze the stochastic response performance under different noise intensities,wind speeds,stiffness coefficients,and electromechanical coupling coefficients,time domain analysis is also conducted to study the performance of the harvester with different parameters.The results reveal that the mean square displacement and voltage increase with increasing the noise intensity and wind speed,larger absolute values of stiffness coefficient correspond to smaller mean square displacement and voltage,and larger electromechanical coupling coefficients can enhance the mean square voltage.Finally,the influence of wind speed and electromechanical coupling coefficient on the stationary probability density function(SPDF)is investigated,revealing the existence of a bimodal distribution under varying environmental conditions.展开更多
Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that as...Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.展开更多
Biological load-bearing materials,like the nacre in shells,have a unique staggered structure that supports their superior mechanical properties.Engineers have been encouraged to imitate it to create load-bearing bio-i...Biological load-bearing materials,like the nacre in shells,have a unique staggered structure that supports their superior mechanical properties.Engineers have been encouraged to imitate it to create load-bearing bio-inspired materials which have excellent properties not present in conventional composites.To create such materials with desirable mechanical properties,the optimum structural parameters combination must be selected.Moreover,the optimal design of bio-inspired composites needs to take into account the trade-offs between various mechanical properties.In this paper,multi-objective optimization models were developed using structural parameters as design variables and mechanical properties as optimization objectives,including stiffness,strength,toughness,and dynamic damping.Using the NSGA-II optimization algorithm,a set of optimal solutions were solved.Additionally,three different structures in natural nacre were introduced in order to utilize the better structure when design bio-inspired materials.The range of optimal solutions that obtained using results from previous research were examined and explained why this collection of optimal solution ranges is better.Also,optimal solutions were compared with the structural features and mechanical properties of real nacre and artificial biomimetic composites to validate our models.Finally,the optimum design strategies can be obtained for nacre-like composites.Our research methodically proposes an optimization method for achieving load-bearing bio-inspired materials with excellent properties and creates a set of optimal solutions from which designers can select the one that best suits their preferences,allowing the fabricated materials to demonstrate preferred performance.展开更多
IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional pro...IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.展开更多
Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep...Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep learning models encounter challenges with optimization,parameter tuning,and handling large-scale,highdimensional data.Bio-inspired algorithms,which mimic natural processes,offer robust optimization capabilities that can enhance NLP performance by improving feature selection,optimizing model parameters,and integrating adaptive learning mechanisms.This review explores the state-of-the-art applications of bio-inspired algorithms—such as Genetic Algorithms(GA),Particle Swarm Optimization(PSO),and Ant Colony Optimization(ACO)—across core NLP tasks.We analyze their comparative advantages,discuss their integration with neural network models,and address computational and scalability limitations.Through a synthesis of existing research,this paper highlights the unique strengths and current challenges of bio-inspired approaches in NLP,offering insights into hybrid models and lightweight,resource-efficient adaptations for real-time processing.Finally,we outline future research directions that emphasize the development of scalable,effective bio-inspired methods adaptable to evolving data environments.展开更多
The scaled suction caisson repre sents an innovative design featuring a bio-inspired sidewall modeled after snake skin,commonly utilized in offshore mooring platforms.In comparison with traditional suction caissons,th...The scaled suction caisson repre sents an innovative design featuring a bio-inspired sidewall modeled after snake skin,commonly utilized in offshore mooring platforms.In comparison with traditional suction caissons,this bio-inspired design demonstrates reduced penetration resistance and enhanced pull-out capacity due to the anisotropic shear behaviors of its sidewall.To investigate the shear behavior of the bio-inspired sidewall under pull-out load,direct shear tests were conducted between the bio-inspired surface and sand.The research demonstrates that the interface shear strength of the bio-inspired surface significantly surpasses that of the smooth surface due to interlocking effects.Additionally,the interface shear strength correlates with the aspect ratio of the bio-inspired surface,shear angle,and particle diameter distribution,with values increasing as the uniformity coefficient Cudecreases,while initially increasing and subsequently decreasing with increases in both aspect ratio and shear angle.The ratio between the interface friction angleδand internal friction angle δ_(s) defines the interface effect factor k.For the bio-inspired surface,the interface effect factor k varies with shear angleβ,ranging from 0.9 to 1.12.The peak value occurs at a shear angleβof 60°,substantially exceeding that of the smooth surface.A method for calculating the relative roughness R_(N) is employed to evaluate the interface roughness of the bio-inspired surface,taking into account scale dimension and particle diameter distribution effects.展开更多
基金Project supported by the National Key Technology R&D Program of China(No.2012BAJ07B03)the National Natural Science Foundation of China(Nos.51178415 and 51578491)
文摘One of the main problems in controlling the shape of active structures （AS） is to determine the actuations that drive the structure from the current state to the target state. Model-based methods such as stochastic search require a known type of load and relatively long computational time, which limits the practical use of AS in civil engineering. Moreover, additive errors may be produced because of the discrepancy between analytic models and real structures. To overcome these limitations, this paper presents a compound system called WAS, which combines AS with a wireless sensor and actuator network （WSAN）. A bio-inspired control framework imitating the activity of the nervous systems of animals is proposed for WAS. A typical example is tested for verification. In the example, a triangular tensegrity prism that aims to maintain its original height is integrated with a WSAN that consists of a central controller, three actuators, and three sensors. The result demonstrates the feasibility of the proposed concept and control framework in cases of unknown loads that include different types, distributions, magnitudes, and directions. The proposed control framework can also act as a supplementary means to improve the efficiency and accuracy of control frameworks based on a common stochastic search.
基金the Natural Science Foundation of China(Project for Young Scientists:Grant No.52105010,Regular Project:Grant No.62173096)Natural Science Foundationof Guangdong Province(Regular Project:Grant No.2025A1515012124,Grant No.2022A1515010327)Guangdong-Hong Kong-Macao Key Laboratory of Multi-scaleInformation Fusion and Collaborative Optimization Control Manufacturing Process.
文摘Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary Soft Tri-Legged Robot(STLR)that improves movement and obstacle-avoidance skills by using a bio-inspired pneumatic artificial muscle(Bubble Artificial Muscles)and a bio-inspired tactile sensor(TacTip).The STLR is activated by BAMs,which are flexible,pneu-matic-driven actuators that provide fine control over forward,backward,and steering movements.Obstacle identification and avoidance are facilitated by the TacTip sensor,which delivers tactile input for traversing unstructured terrains.We delineate the mechanical features of the BAMs,assess the functionality of the robot's legs,and elaborate on the incorpora-tion of the tactile sensing system.Experimental results demonstrate that the STLR can effectively achieve multi-directional flexible movement and obstacle avoidance through a cross-modal perception-actuation mechanism.This study highlights the promise of soft robotics for search and rescue,medical aid,and autonomous exploration,while delineating difficulties and opportunities for future improvements in functionality and efficiency.
基金Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam for supporting this study。
文摘Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.
基金supported in part by the Guangdong Provincial Universities'Characteristic Innovation Project under Grant 2024KTSCX360in part by the Guangdong Educational Science Planning Project under Grant 2023GXJK837.
文摘Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.
基金the financial support from the Research Institute for Advanced Manufacturing(RIAM)of The Hong Kong Polytechnic University(project Nos.1-CD9F and 1-CDK3)the Research Grants Council(RGC)of Hong Kong(project Nos.25200424 and 15206223)+2 种基金the GuangDong Basic and Applied Basic Research Foundation(project No.2023A1515110709)the Startup fund(project No.1-BE9L)of the Hong Kong Polytechnic Universitysupported by grant from the Research Committee of the Hong Kong Polytechnic University under student account code RN5Y.
文摘Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this review,we systematically survey the basics of MHMRs,from propulsion mechanism,magnetization and control methods to biomedical applications,aiming to provide readers with an easily understandable overview and fundamental knowledge on implementing MHMRs.The MHMRs are actuated by rotating magnetic fields,achieving steering and rotation through magnetic torque,and converting rotation into forward motion through the helical structure.Magnetization methods for MHMRs are reviewed into three types:attaching magnets,magnetic coatings,and magnetic powder doping.Additionally,this review discusses the control methods for MHMRs,covering imaging techniques,path tracking control—including classical control algorithms and increasingly popular learning-based methods,and swarm control.Subsequently,a comprehensive survey is conducted on the biomedical applications of MHMRs in the treatment of vascular diseases,drug delivery,cell delivery,and their integration with catheters.We finally provide a perspective about future challenges in MHMR research,including enhancing functional design capabilities,developing swarm-assisted independent control mechanisms,refining in vivo imaging techniques,and ensuring robust biocompatibility for safe medical use.
基金Supported by the National Natural Science Foundation of China (50505017)Fok Ying Tung Edu-cation Foundation (111056)+1 种基金the Innovative and Excellent Foundation for Doctoral Dissertation of Nanjing University of Aeronautics and Astronautics (BCXJ08-07)the New Century Excellent Talents in University,China (NCET-08)~~
文摘Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.
基金The National Natural Science Foundation of China(62203015,62233001,62273351)The Beijing Natural Science Foundation(4242038)。
文摘This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task allocation for vigilance roles and the coverage planning of the perception ranges.Firstly,vigilance behavioral patterns and processes in animal populations within natural habitats are investigated.Inspired by these biological vigilance behaviors,an efficient vigilance task allocation model for MAS is proposed.Secondly,the subsequent optimization of task layouts can achieve efficient surveillance coverage with fewer agents,minimizing resource consumption.Thirdly,an improved particle swarm optimization(IPSO)algorithm is proposed,which incorporates fitness-driven adaptive inertia weight dynamics.According to simulation analysis and comparative studies,optimal parameter configurations for genetic algorithm(GA)and IPSO are determined.Finally,the results indicate the proposed IPSO's superior performance to both GA and standard particle swarm optimization(PSO)in vigilance task allocation optimization,with satisfying advantages in computational efficiency and solution quality.
基金partially supported by the National Nature Science Foundation of China(Grant No.51309062)
文摘The formation control problem for underactuated unmanned surface vehicles(USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law,and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller.
文摘A bio-inspired global finite time control using global fast-terminal sliding mode controller and radial basis function network is presented in this article,to address the attitude tracking control problem of the three degree-of-freedom four-rotor hover system.The proposed controller provides convergence of system states in a predetermined finite time and estimates the unmodeled dynamics of the four-rotor system.Dynamic model of the four-rotor system is derived with Newton’s force equations.The unknown dynamics of four-rotor systems are estimated using Radial basis function.The bio-inspired global fast terminal sliding mode controller is proposed to provide chattering free finite time error convergence and to provide optimal tracking of the attitude angles while being subjected to unknown dynamics.The global stability proof of the designed controller is provided on the basis of Lyapunov stability theorem.The proposed controller is validated by(i)conducting an experiment through implementing it on the laboratory-based hover system,and(ii)through simulations.Performance of the proposed control scheme is also compared with classical and intelligent controllers.The performance comparison exhibits that the designed controller has quick transient response and improved chattering free steady state performance.The proposed bioinspired global fast terminal sliding mode controller offers improved estimation and better tracking performance than the traditional controllers.In addition,the proposed controller is computationally cost effective and can be implanted on multirotor unmanned air vehicles with limited computational processing capabilities.
文摘Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering applications.The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System Algorithm(ACSA).The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this process.The work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions,identified as classical benchmark functions.The method was subsequently examined by application to 12 CEC 2022 benchmark problems of different complexities.Furthermore,the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches,including evolutionary,human,physics,and swarm-based.Subsequently,a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing literature.The results show that the ACSA strategy can quickly reach the global optimum,avoid getting trapped in local optima,and effectively maintain a balance between exploration and exploitation.ACSA outperformed 42 algorithms statistically,according to post-hoc tests.It also outperformed 9 algorithms quantitatively.The study concludes that ACSA offers competitive solutions in comparison to popüler methods.
基金supported by the Basic Research Development Program of China(No.JCKY2021607B036)the National Natural Science Foundation of China(No.52275512).
文摘There is an urgent need for the application of broadband Microwave Absorption(MA)structures on the leading edges of aircraft wings,which requires the MA structures to possess both the broadband MA performance and great surface conformability.To meet these requirements,we designed and fabricated a flexible bioinspired meta-structure with ultra-broadband MA,thin thickness and excellent surface conformality.The carbonyl iron powder-carbon nanotubes-polydimethylsiloxane composite was synthesized by physical blending method for fabricating the MA meta-structure.Through geometry-electromagnetic optimal design by heuristic optimization algorithm,the meta-structure mimicking to the nipple photonic nanostructures on the eyes of moth can achieve ultra-broadband MA performance of 35.14 GHz MA bandwidth(reflection loss≤–10 dB),covering 4.86–40.00 GHz,with thickness of only 4.3 mm.Through simple fabrication processes,the meta-structure has been successfully fabricated and bonded on wings’leading edges,exhibiting excellent surface conformability.Furthermore,the designed flexible MA meta-structure possesses significant Radar Cross-Section(RCS)reduction capability,as demonstrated by the RCS analysis of an unmanned aerial vehicle.This flexible ultra-broadband MA meta-structure provides an outstanding candidate to meet the radar stealth requirement of variable curvature structures on aircraft.
基金support by the National Natural Science Foundation of China(No.62073217,No.61871266)the Fund of the Ministry of Education of the People’s Republic of China(6141A02022607,6141A020227)the Fund of the Professional Technical Service Platform of Shanghai(19DZ2291103).
文摘The development of a tailless Flapping Wing Micro Aerial Vehicle(FWMAV)inspired by the hummingbird is presented in this work.By implementing mechanical simplifications,it is possible to use planar machining technology for manufacturing of the FWMAV’s body,greatly reducing assembly errors.Traditionally,studies on flapping wing aircraft are limited to open-loop wing kinematics control.In this work,an instantaneous closed-loop wing trajectory tracking control system is introduced to minimize wings’trajectory tracking errors.The control system is based on Field-Oriented Control(FOC)with a loop shaping compensation technique near the flapping frequency.Through frequency analysis,the loop shaping compensator ensures the satisfactory bandwidth and performance for the closed-loop flapping system.To implement the proposed controller,a compact autopilot board integrated with FOC hardware is designed,weighing only 2.5 g.By utilizing precise wing trajectory tracking control,the hummingbird-inspired FWMAV demonstrates superior ability to resist external disturbances and exhibits reduced attitude tracking errors during hovering flight compared to the open-loop wing motion.
文摘McKibben muscles are increasingly used in many robotic applications due to their advantages of lightweight,compliant,and skeletal muscles-like behaviours.However,there are still huge challenges in the motion control of McKibben muscles due to the system nonlinearity(e.g.,hysteresis)and model uncertainties.To investigate the control issues,a soft artificial arm actuated by an antagonistic pair of McKibben muscles,mimicking the biological structure of skeleton-muscle systems,is developed.Inspired by the biological motor control capability that humans can control and coordinate a group of muscles to achieve complex motions,a cerebellum-like controller based on Spiking Neural Networks(SNNs)is employed for the motion control of the developed artificial arm.Benefit from the employment of the SNN-based cerebellar model,the proposed control scheme provides online adaptive learning capability,good computational efficiency,fast response,and strong robustness.Finally,several simulations and experiments are conducted subject to different environmental disturbances.Both simulation and experimental results verify that the proposed method can achieve good tracking performance,adaptability,and strong robustness.
文摘To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subjected to Gaussian white noise and galloping excitation,simulating the flapping pattern of a seagull and its interaction with wind force.The equivalent linearization method is utilized to convert the original nonlinear model into the Itôstochastic differential equation by minimizing the mean squared error.Then,the second-order steady-state moments about the displacement,velocity,and voltage are derived by combining the moment analysis theory.The theoretical results are simulated numerically to analyze the stochastic response performance under different noise intensities,wind speeds,stiffness coefficients,and electromechanical coupling coefficients,time domain analysis is also conducted to study the performance of the harvester with different parameters.The results reveal that the mean square displacement and voltage increase with increasing the noise intensity and wind speed,larger absolute values of stiffness coefficient correspond to smaller mean square displacement and voltage,and larger electromechanical coupling coefficients can enhance the mean square voltage.Finally,the influence of wind speed and electromechanical coupling coefficient on the stationary probability density function(SPDF)is investigated,revealing the existence of a bimodal distribution under varying environmental conditions.
基金Supported by Beijing Natural Science Foundation(Grant No.L231004)Young Elite Scientists Sponsorship Program by CAST(Grant No.2022QNRC001)+2 种基金Fundamental Research Funds for the Central Universities(Grant No.2025JBMC039)National Key Research and Development Program(Grant No.2022YFC2805200)National Natural Science Foundation of China(Grant No.52371338).
文摘Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.
基金Supported by National Natural Science Foundation of China(Grant Nos.52222505,52321002)Shanghai Municipal Natural Science Foundation o China(Grant No.23ZR1415500)。
文摘Biological load-bearing materials,like the nacre in shells,have a unique staggered structure that supports their superior mechanical properties.Engineers have been encouraged to imitate it to create load-bearing bio-inspired materials which have excellent properties not present in conventional composites.To create such materials with desirable mechanical properties,the optimum structural parameters combination must be selected.Moreover,the optimal design of bio-inspired composites needs to take into account the trade-offs between various mechanical properties.In this paper,multi-objective optimization models were developed using structural parameters as design variables and mechanical properties as optimization objectives,including stiffness,strength,toughness,and dynamic damping.Using the NSGA-II optimization algorithm,a set of optimal solutions were solved.Additionally,three different structures in natural nacre were introduced in order to utilize the better structure when design bio-inspired materials.The range of optimal solutions that obtained using results from previous research were examined and explained why this collection of optimal solution ranges is better.Also,optimal solutions were compared with the structural features and mechanical properties of real nacre and artificial biomimetic composites to validate our models.Finally,the optimum design strategies can be obtained for nacre-like composites.Our research methodically proposes an optimization method for achieving load-bearing bio-inspired materials with excellent properties and creates a set of optimal solutions from which designers can select the one that best suits their preferences,allowing the fabricated materials to demonstrate preferred performance.
文摘IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.
基金supported by AIT Laboratory,FPT University,Danang Campus,Vietnam,2024.
文摘Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep learning models encounter challenges with optimization,parameter tuning,and handling large-scale,highdimensional data.Bio-inspired algorithms,which mimic natural processes,offer robust optimization capabilities that can enhance NLP performance by improving feature selection,optimizing model parameters,and integrating adaptive learning mechanisms.This review explores the state-of-the-art applications of bio-inspired algorithms—such as Genetic Algorithms(GA),Particle Swarm Optimization(PSO),and Ant Colony Optimization(ACO)—across core NLP tasks.We analyze their comparative advantages,discuss their integration with neural network models,and address computational and scalability limitations.Through a synthesis of existing research,this paper highlights the unique strengths and current challenges of bio-inspired approaches in NLP,offering insights into hybrid models and lightweight,resource-efficient adaptations for real-time processing.Finally,we outline future research directions that emphasize the development of scalable,effective bio-inspired methods adaptable to evolving data environments.
基金supported by the National Natural Science Foundation of China(Grant Nos.52371301 and 52471289)。
文摘The scaled suction caisson repre sents an innovative design featuring a bio-inspired sidewall modeled after snake skin,commonly utilized in offshore mooring platforms.In comparison with traditional suction caissons,this bio-inspired design demonstrates reduced penetration resistance and enhanced pull-out capacity due to the anisotropic shear behaviors of its sidewall.To investigate the shear behavior of the bio-inspired sidewall under pull-out load,direct shear tests were conducted between the bio-inspired surface and sand.The research demonstrates that the interface shear strength of the bio-inspired surface significantly surpasses that of the smooth surface due to interlocking effects.Additionally,the interface shear strength correlates with the aspect ratio of the bio-inspired surface,shear angle,and particle diameter distribution,with values increasing as the uniformity coefficient Cudecreases,while initially increasing and subsequently decreasing with increases in both aspect ratio and shear angle.The ratio between the interface friction angleδand internal friction angle δ_(s) defines the interface effect factor k.For the bio-inspired surface,the interface effect factor k varies with shear angleβ,ranging from 0.9 to 1.12.The peak value occurs at a shear angleβof 60°,substantially exceeding that of the smooth surface.A method for calculating the relative roughness R_(N) is employed to evaluate the interface roughness of the bio-inspired surface,taking into account scale dimension and particle diameter distribution effects.
