Microrobotic systems are emerging as transformative technology for minimally invasive medicine,driven by innovations in actuation mechanisms,advanced fabrication paradigms,and multifunctional system integration.This c...Microrobotic systems are emerging as transformative technology for minimally invasive medicine,driven by innovations in actuation mechanisms,advanced fabrication paradigms,and multifunctional system integration.This comprehensive review analyzes the evolution of microrobotic technologies through three critical dimensions:(1)actuation modalities,including magnetic,optical,acoustic,chemical,and biological actuation,with a focus on the synergistic advantages of hybrid actuation strategies in complex internal physiological environments;(2)Fabrication methods cover technolo-gies such as photolithography,microinjection molding,self-assembly,and 3D printing,emphasizing innovative strategies involving multi-technology integration and collaborative manufacturing of bio/non-bio hybrid materials;(3)Internal phys-iological applications involve disease diagnosis,targeted drug delivery,minimally invasive surgery,tissue engineering,and cell manipulation,highlighting the broad prospects of microrobots in precision medicine.Despite remarkable progress,critical challenges remain,including low actuation efficiency,as seen in acoustic systems,limited biocompatibility,exem-plified by the toxicity of hydrogen peroxide in chemical actuation,delayed clinical translation,and other related challenges that must be addressed to advance the field.展开更多
In this research,a comparative analysis was conducted on the performance and efficiency of the dual-anchor soft robot(DASR)and the extension-contraction soft robot(ECSR).These robots were constructed by imitating the ...In this research,a comparative analysis was conducted on the performance and efficiency of the dual-anchor soft robot(DASR)and the extension-contraction soft robot(ECSR).These robots were constructed by imitating the locomotion of razor clams.The penetration force for extension actuators and the anchorage force for expansion actuators in dry sand with distinct relative densities were tested by differentiating input air pressure and length-to-diameter ratios(λ).On the basis of the findings,a DASR and an ECSR were developed.DASR comprised two expansion actuators as the head and the tail segments at two ends,and one extension actuator as the middle segment.ECSR was composed of an extension actuator.A method based on the force equilibrium was introduced to ascertain and adjust the geometric parameters(length of each segment)of DASR.The burrowing-out performance and efficiency of DASR and ECSR in sands with distinct relative densities were explored.The results revealed that DASR exhibited high efficiency in dense sand in terms of lower time of burrowing-out,slip-to-advancement ratio,and cost of transport.ECSR might perform better in looser sand in terms of higher average burrowing-out velocity,higher advancement in each cycle,and lower energy consumption.However,it had larger slips than DASR.DASR could realize steady advancement and net displacement in each cycle and effectively decrease slips.These findings demonstrate the benefits and usability of the dual-anchor motion and offer new insights into the application of the dual-anchor mechanism in the burrowing of robots.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
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
The capability of whole-body proprioception,e.g.,pose estimation,is important for the control and interaction of continuum robots.However,existing pose estimation methods are often simplified through geometric assumpt...The capability of whole-body proprioception,e.g.,pose estimation,is important for the control and interaction of continuum robots.However,existing pose estimation methods are often simplified through geometric assumptions,primarily due to constraints such as computational and sensor deployment costs.We propose an explicit posture estimation method through a neural network,and implement it using an embedded camera for vision-based proprioception.We design a continuous location encoding neural network(LENN)by encoding continuous locational information.The LENN can capture deformation from changes in internal texture observed by an integrated camera,and output pose information—both position and orientation—for any point along the robot backbone,rather than only discrete points.Compared with interpolation-based estimation using a reduced model,our method reduces single-point estimation error by 33.6%.Furthermore,a systematic evaluation of hardware configurations demonstrates that our prototype achieves sub-millimetre accuracy in shape estimation(0.383 mm)while maintaining real-time inference speeds below 12 ms per frame.By combining a learning-based approach with a simple mechanical design,our method leverages internal visual information to estimate the whole-body pose,providing an effective solution for accurate shape estimation in continuum robots.展开更多
Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This stu...Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.展开更多
Most existing path planning approaches rely on discrete expansions or localized heuristics that can lead to extended re-planning,inefficient detours,and limited adaptability to complex obstacle distributions.These iss...Most existing path planning approaches rely on discrete expansions or localized heuristics that can lead to extended re-planning,inefficient detours,and limited adaptability to complex obstacle distributions.These issues are particularly pronounced when navigating cluttered or large-scale environments that demand both global coverage and smooth trajectory generation.To address these challenges,this paper proposes a Wave Water Simulator(WWS)algorithm,leveraging a physically motivated wave equation to achieve inherently smooth,globally consistent path planning.In WWS,wavefront expansions naturally identify safe corridors while seamlessly avoiding local minima,and selective corridor focusing reduces computational overhead in large or dense maps.Comprehensive simulations and real-world validations-encompassing both indoor and outdoor scenarios-demonstrate that WWS reduces path length by 2%-13%compared to conventional methods,while preserving gentle curvature and robust obstacle clearance.Furthermore,WWS requires minimal parameter tuning across diverse domains,underscoring its broad applicability to warehouse robotics,field operations,and autonomous service vehicles.These findings confirm that the proposed wave-based framework not only bridges the gap between local heuristics and global coverage but also sets a promising direction for future extensions toward dynamic obstacle scenarios and multi-agent coordination.展开更多
In recent years,the rapid advancement of artificial intelligence(AI)has fostered deep integration between large AI models and robotic technology.Robots such as robotic dogs capable of carrying heavy loads on mountaino...In recent years,the rapid advancement of artificial intelligence(AI)has fostered deep integration between large AI models and robotic technology.Robots such as robotic dogs capable of carrying heavy loads on mountainous terrain or performing waste disposal tasks and humanoid robots that can execute high-precision component installations have gradually reached the public eye,raising expectations for embodied intelligent robots.展开更多
Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser...Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser in recent years,particularly in the area of humanoid robots.展开更多
Gecko-inspired robots have significant potential applications;however,deviations in the yaw direction during locomotion are inevitable for legged robots that lack external sensing.These deviations cause the robot to s...Gecko-inspired robots have significant potential applications;however,deviations in the yaw direction during locomotion are inevitable for legged robots that lack external sensing.These deviations cause the robot to stray from its intended path.Therefore,a cost-effective and straightforward solution is essential for reducing this deviation.In nature,the tail is often used to maintain balance and stability.Similarly,it has been used in robots to improve manoeuvrability and stability.Our aim is to reduce this deviation using a morphological computation approach,specifically by adding a tail.To test this hypothesis,we investigated four different tails(rigid plate,rigid gecko-shaped,soft plate,and soft gecko-shaped)and assessed the deviation of the robot with these tails on different slopes.Additionally,to evaluate the influence of different tail parameters,such as material,shape,and linkage,we investigated the locomotion performance in terms of the robot's climbing speed on slopes,its ability to turn at narrow corners,and the resistance of the tails to external disturbances.A new auto-reset joint was designed to ensure that a disturbed tail could be quickly reset.Our results demonstrate that the yaw deviation of the robot can be reduced by applying a tail.Among the four tails,the soft gecko-shaped tail was the most effective for most tasks.In summary,our findings demonstrate the functional role of the tail in reducing yaw deviation,improving climbing ability and stability and provide a reference for selecting the most suitable tail for geckoinspired robots.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
Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptabilit...Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.展开更多
This article provides a comprehensive exploration of the current research landscape in the field of soft actuation technology applied to bio-inspired soft robots. In sharp contrast to their conventional rigid counterp...This article provides a comprehensive exploration of the current research landscape in the field of soft actuation technology applied to bio-inspired soft robots. In sharp contrast to their conventional rigid counterparts, bio-inspired soft robots are primarily constructed from flexible materials, conferring upon them remarkable adaptability and flexibility to execute a multitude of tasks in complex environments. However, the classification of their driving technology poses a significant challenge owing to the diverse array of employed driving mechanisms and materials. Here, we classify several common soft actuation methods from the perspectives of the sources of motion in bio-inspired soft robots and their bio-inspired objects, effectively filling the classification system of soft robots, especially bio-inspired soft robots. Then, we summarize the driving principles and structures of various common driving methods from the perspective of bionics, and discuss the latest developments in the field of soft robot actuation from the perspective of driving modalities and methodologies. We then discuss the application directions of bio-inspired soft robots and the latest developments in each direction. Finally, after an in-depth review of various soft bio-inspired robot driving technologies in recent years, we summarize the issues and challenges encountered in the advancement of soft robot actuation technology.展开更多
The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have bec...The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have become a pivotal production tool in this context.Since the arm span of a single robot usually does not exceed 3 meters,it is not competent for producing large-scale building components.Accordingly,the extension of the robot,s working range is often achieved by external axes.Nevertheless,the coupling control of external axes and robots and their kinematic solution have become key challenges.The primary technical difficulties include customized construction robots,automatic solutions for external axes,fixed axis joints,and specific motion mode control.This paper proposes solutions to these difficulties,introduces the relevant basic concepts and algorithms in detail,and encapsulates these robotics principles and algorithm processes into the Grasshopper plug-in commonly used by architects to form the FURobot software platform.This platform effectively solves the above problems,lowers the threshold for architects,and improves production efficiency.The effectiveness of the algorithm and software in this paper is verified through simulation experiments.展开更多
The rapid evolution of industrial robots from automation tools to intelligent systems marks a pivotal shift in manufacturing practices within the framework of Industry 4.0.Industrial robots,once limited to repetitive ...The rapid evolution of industrial robots from automation tools to intelligent systems marks a pivotal shift in manufacturing practices within the framework of Industry 4.0.Industrial robots,once limited to repetitive tasks on assembly lines,are now increasingly powered by advanced technologies such as Artificial Intelligence(AI),machine learning,and the Internet of Things(IoT),enabling them to perform complex,adaptive tasks in real-time.This paper explores the technological advancements that have transformed industrial robots,highlighting the integration of AI,smart sensors,and autonomous systems.Furthermore,it examines the implications of this paradigm shift for industries,human-robot collaboration,and the workforce.While intelligent robots promise greater efficiency,flexibility,and safety in manufacturing,challenges regarding implementation,economic impact,and ethical considerations remain significant.The paper concludes by looking at the future trends in robotics and their potential to reshape the global industrial landscape.展开更多
Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover pr...Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover prevention strategy is proposed,utilizing a single‐gimbal control moment gyro(SGCMG),to stabilize typical agricultural robots and prevent potential rollovers.To match the free oscillation of the pivot front axle,a novel recovery torque model of the coupled robot‐SGCMG system is established,in which two patterns are introduced to refine the rollover process with uncertain parameters.Additionally,a lateral stability index is adopted and analyzed to assess the hazard level of potential rollovers.Aimed at handling uncertain parameters and hazard levels,an adaptive backstepping control strategy is developed for real‐time anti‐rollover implementation.Within this strategy,control gains are adaptively tuned based on theoretical derivations,thereby suppressing rollover tendency while minimizing tuning effort.For verification,a scaled experimental platform,designed according to similarity theory,is constructed to ensure safety of personnel and equipment.Experimental results show that the proposed method can precisely regulate the output torque of the gyro,rapidly and effectively mitigating the risk of imminent rollover.This method provides a promising solution for wheeled robot stability and a theoretical basis for advanced safety control in agricultural robotics.展开更多
A type of novel biodegradable fibers,made from magnetic particles and the patient’s own blood,promises an immune-evading brain cancer therapy with minimal invasion.
Traditional hybrid crop breeding faces inefficiencies due to labor-intensive manual pollination-especially for crops like tomatoes and soybeans with complex flowers.Researchers at the Institute of Genetics and Develop...Traditional hybrid crop breeding faces inefficiencies due to labor-intensive manual pollination-especially for crops like tomatoes and soybeans with complex flowers.Researchers at the Institute of Genetics and Developmental Biology(IGDB),Chinese Academy of Sciences,have developed GEAIR(Genome Editing with Artificial-Intelligence-based Robots),an AI-robotic system that pollinates gene-edited plants 24/7.展开更多
The ability of mobile robots to plan and execute a path is foundational to various path-planning challenges,particularly Coverage Path Planning.While this task has been typically tackled with classical algorithms,thes...The ability of mobile robots to plan and execute a path is foundational to various path-planning challenges,particularly Coverage Path Planning.While this task has been typically tackled with classical algorithms,these often struggle with flexibility and adaptability in unknown environments.On the other hand,recent advances in Reinforcement Learning offer promising approaches,yet a significant gap in the literature remains when it comes to generalization over a large number of parameters.This paper presents a unified,generalized framework for coverage path planning that leverages value-based deep reinforcement learning techniques.The novelty of the framework comes from the design of an observation space that accommodates different map sizes,an action masking scheme that guarantees safety and robustness while also serving as a learning-fromdemonstration technique during training,and a unique reward function that yields value functions that are size-invariant.These are coupled with a curriculum learning-based training strategy and parametric environment randomization,enabling the agent to tackle complete or partial coverage path planning with perfect or incomplete knowledge while generalizing to different map sizes,configurations,sensor payloads,and sub-tasks.Our empirical results show that the algorithm can perform zero-shot learning scenarios at a near-optimal level in environments that follow a similar distribution as during training,outperforming a greedy heuristic by sixfold.Furthermore,in out-of-distribution environments,our method surpasses existing state-of-the-art algorithms in most zero-shot and all few-shot scenarios,paving the way for generalizable and adaptable path-planning algorithms.展开更多
基金National Natural Science Foundation of China(Grant No.61903157)the Foundation of State Key Laboratory of Robotics(Grand No.2024-O08).
文摘Microrobotic systems are emerging as transformative technology for minimally invasive medicine,driven by innovations in actuation mechanisms,advanced fabrication paradigms,and multifunctional system integration.This comprehensive review analyzes the evolution of microrobotic technologies through three critical dimensions:(1)actuation modalities,including magnetic,optical,acoustic,chemical,and biological actuation,with a focus on the synergistic advantages of hybrid actuation strategies in complex internal physiological environments;(2)Fabrication methods cover technolo-gies such as photolithography,microinjection molding,self-assembly,and 3D printing,emphasizing innovative strategies involving multi-technology integration and collaborative manufacturing of bio/non-bio hybrid materials;(3)Internal phys-iological applications involve disease diagnosis,targeted drug delivery,minimally invasive surgery,tissue engineering,and cell manipulation,highlighting the broad prospects of microrobots in precision medicine.Despite remarkable progress,critical challenges remain,including low actuation efficiency,as seen in acoustic systems,limited biocompatibility,exem-plified by the toxicity of hydrogen peroxide in chemical actuation,delayed clinical translation,and other related challenges that must be addressed to advance the field.
基金financially supported by the Natural Science Foundation of Jiangsu Province,China(No.BK 20221502)the National Natural Science Foundation of China(No.42477147)。
文摘In this research,a comparative analysis was conducted on the performance and efficiency of the dual-anchor soft robot(DASR)and the extension-contraction soft robot(ECSR).These robots were constructed by imitating the locomotion of razor clams.The penetration force for extension actuators and the anchorage force for expansion actuators in dry sand with distinct relative densities were tested by differentiating input air pressure and length-to-diameter ratios(λ).On the basis of the findings,a DASR and an ECSR were developed.DASR comprised two expansion actuators as the head and the tail segments at two ends,and one extension actuator as the middle segment.ECSR was composed of an extension actuator.A method based on the force equilibrium was introduced to ascertain and adjust the geometric parameters(length of each segment)of DASR.The burrowing-out performance and efficiency of DASR and ECSR in sands with distinct relative densities were explored.The results revealed that DASR exhibited high efficiency in dense sand in terms of lower time of burrowing-out,slip-to-advancement ratio,and cost of transport.ECSR might perform better in looser sand in terms of higher average burrowing-out velocity,higher advancement in each cycle,and lower energy consumption.However,it had larger slips than DASR.DASR could realize steady advancement and net displacement in each cycle and effectively decrease slips.These findings demonstrate the benefits and usability of the dual-anchor motion and offer new insights into the application of the dual-anchor mechanism in the burrowing of robots.
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 by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
基金supported by the National Natural Science Foundation of China(Grant Nos.52188102,52505008)the National Key Research and Development Program of China(Grant No.2024YFB4707902)。
文摘The capability of whole-body proprioception,e.g.,pose estimation,is important for the control and interaction of continuum robots.However,existing pose estimation methods are often simplified through geometric assumptions,primarily due to constraints such as computational and sensor deployment costs.We propose an explicit posture estimation method through a neural network,and implement it using an embedded camera for vision-based proprioception.We design a continuous location encoding neural network(LENN)by encoding continuous locational information.The LENN can capture deformation from changes in internal texture observed by an integrated camera,and output pose information—both position and orientation—for any point along the robot backbone,rather than only discrete points.Compared with interpolation-based estimation using a reduced model,our method reduces single-point estimation error by 33.6%.Furthermore,a systematic evaluation of hardware configurations demonstrates that our prototype achieves sub-millimetre accuracy in shape estimation(0.383 mm)while maintaining real-time inference speeds below 12 ms per frame.By combining a learning-based approach with a simple mechanical design,our method leverages internal visual information to estimate the whole-body pose,providing an effective solution for accurate shape estimation in continuum robots.
基金supported by the Malaysia Ministry of Higher Education under Fundamental Research Grant Scheme with Project Code:FRGS/1/2024/TK07/USM/02/3.
文摘Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.
文摘Most existing path planning approaches rely on discrete expansions or localized heuristics that can lead to extended re-planning,inefficient detours,and limited adaptability to complex obstacle distributions.These issues are particularly pronounced when navigating cluttered or large-scale environments that demand both global coverage and smooth trajectory generation.To address these challenges,this paper proposes a Wave Water Simulator(WWS)algorithm,leveraging a physically motivated wave equation to achieve inherently smooth,globally consistent path planning.In WWS,wavefront expansions naturally identify safe corridors while seamlessly avoiding local minima,and selective corridor focusing reduces computational overhead in large or dense maps.Comprehensive simulations and real-world validations-encompassing both indoor and outdoor scenarios-demonstrate that WWS reduces path length by 2%-13%compared to conventional methods,while preserving gentle curvature and robust obstacle clearance.Furthermore,WWS requires minimal parameter tuning across diverse domains,underscoring its broad applicability to warehouse robotics,field operations,and autonomous service vehicles.These findings confirm that the proposed wave-based framework not only bridges the gap between local heuristics and global coverage but also sets a promising direction for future extensions toward dynamic obstacle scenarios and multi-agent coordination.
文摘In recent years,the rapid advancement of artificial intelligence(AI)has fostered deep integration between large AI models and robotic technology.Robots such as robotic dogs capable of carrying heavy loads on mountainous terrain or performing waste disposal tasks and humanoid robots that can execute high-precision component installations have gradually reached the public eye,raising expectations for embodied intelligent robots.
文摘Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser in recent years,particularly in the area of humanoid robots.
基金supported by the National Key Research&Development Program of China(Grant No.2020YFB1313504)the State Key Laboratory of Mechanics and Control for Aerospace Structures of Nanjing University of Aeronautics and Astronautics.
文摘Gecko-inspired robots have significant potential applications;however,deviations in the yaw direction during locomotion are inevitable for legged robots that lack external sensing.These deviations cause the robot to stray from its intended path.Therefore,a cost-effective and straightforward solution is essential for reducing this deviation.In nature,the tail is often used to maintain balance and stability.Similarly,it has been used in robots to improve manoeuvrability and stability.Our aim is to reduce this deviation using a morphological computation approach,specifically by adding a tail.To test this hypothesis,we investigated four different tails(rigid plate,rigid gecko-shaped,soft plate,and soft gecko-shaped)and assessed the deviation of the robot with these tails on different slopes.Additionally,to evaluate the influence of different tail parameters,such as material,shape,and linkage,we investigated the locomotion performance in terms of the robot's climbing speed on slopes,its ability to turn at narrow corners,and the resistance of the tails to external disturbances.A new auto-reset joint was designed to ensure that a disturbed tail could be quickly reset.Our results demonstrate that the yaw deviation of the robot can be reduced by applying a tail.Among the four tails,the soft gecko-shaped tail was the most effective for most tasks.In summary,our findings demonstrate the functional role of the tail in reducing yaw deviation,improving climbing ability and stability and provide a reference for selecting the most suitable tail for geckoinspired robots.
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the National Key R&D Program of China(No.2023YFE0208700)National Natural Sci-ence Foundation of China(No.92163109 and 52072095)+7 种基金Shenzhen Science and Technology Program(No.RCJC20231211090000001,GXWD20231129101105001)the National Natural Science Foundation of China(No.52205590)the Natural Science Foundation of Jiangsu Province(No.BK20220834)the Start-up Research Fund of Southeast University(No.RF1028623098)the State Key Laboratory of Robotics and Systems(HIT)(No.SKLRS-2024-KF-11)National Natural Science Foundation of China(No.52202348)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011491)Shenzhen Science and Technology Program(Nos.GXWD20220818224716001,KJZD20231023100302006).
文摘Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.
基金Fundamental Research Funds for the Central Universities(No.2024JBMC011)Aeronautical Science Foundation of China(No.2024Z0560M5001).
文摘This article provides a comprehensive exploration of the current research landscape in the field of soft actuation technology applied to bio-inspired soft robots. In sharp contrast to their conventional rigid counterparts, bio-inspired soft robots are primarily constructed from flexible materials, conferring upon them remarkable adaptability and flexibility to execute a multitude of tasks in complex environments. However, the classification of their driving technology poses a significant challenge owing to the diverse array of employed driving mechanisms and materials. Here, we classify several common soft actuation methods from the perspectives of the sources of motion in bio-inspired soft robots and their bio-inspired objects, effectively filling the classification system of soft robots, especially bio-inspired soft robots. Then, we summarize the driving principles and structures of various common driving methods from the perspective of bionics, and discuss the latest developments in the field of soft robot actuation from the perspective of driving modalities and methodologies. We then discuss the application directions of bio-inspired soft robots and the latest developments in each direction. Finally, after an in-depth review of various soft bio-inspired robot driving technologies in recent years, we summarize the issues and challenges encountered in the advancement of soft robot actuation technology.
基金National Key R&D Program of China(Nos.2023YFC3806900,2022YFE0141400)。
文摘The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have become a pivotal production tool in this context.Since the arm span of a single robot usually does not exceed 3 meters,it is not competent for producing large-scale building components.Accordingly,the extension of the robot,s working range is often achieved by external axes.Nevertheless,the coupling control of external axes and robots and their kinematic solution have become key challenges.The primary technical difficulties include customized construction robots,automatic solutions for external axes,fixed axis joints,and specific motion mode control.This paper proposes solutions to these difficulties,introduces the relevant basic concepts and algorithms in detail,and encapsulates these robotics principles and algorithm processes into the Grasshopper plug-in commonly used by architects to form the FURobot software platform.This platform effectively solves the above problems,lowers the threshold for architects,and improves production efficiency.The effectiveness of the algorithm and software in this paper is verified through simulation experiments.
文摘The rapid evolution of industrial robots from automation tools to intelligent systems marks a pivotal shift in manufacturing practices within the framework of Industry 4.0.Industrial robots,once limited to repetitive tasks on assembly lines,are now increasingly powered by advanced technologies such as Artificial Intelligence(AI),machine learning,and the Internet of Things(IoT),enabling them to perform complex,adaptive tasks in real-time.This paper explores the technological advancements that have transformed industrial robots,highlighting the integration of AI,smart sensors,and autonomous systems.Furthermore,it examines the implications of this paradigm shift for industries,human-robot collaboration,and the workforce.While intelligent robots promise greater efficiency,flexibility,and safety in manufacturing,challenges regarding implementation,economic impact,and ethical considerations remain significant.The paper concludes by looking at the future trends in robotics and their potential to reshape the global industrial landscape.
基金supported by the National Natural Science Foundation of China(No.52175259)the 2115 Talent Development Program of China Agricultural University.
文摘Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover prevention strategy is proposed,utilizing a single‐gimbal control moment gyro(SGCMG),to stabilize typical agricultural robots and prevent potential rollovers.To match the free oscillation of the pivot front axle,a novel recovery torque model of the coupled robot‐SGCMG system is established,in which two patterns are introduced to refine the rollover process with uncertain parameters.Additionally,a lateral stability index is adopted and analyzed to assess the hazard level of potential rollovers.Aimed at handling uncertain parameters and hazard levels,an adaptive backstepping control strategy is developed for real‐time anti‐rollover implementation.Within this strategy,control gains are adaptively tuned based on theoretical derivations,thereby suppressing rollover tendency while minimizing tuning effort.For verification,a scaled experimental platform,designed according to similarity theory,is constructed to ensure safety of personnel and equipment.Experimental results show that the proposed method can precisely regulate the output torque of the gyro,rapidly and effectively mitigating the risk of imminent rollover.This method provides a promising solution for wheeled robot stability and a theoretical basis for advanced safety control in agricultural robotics.
文摘A type of novel biodegradable fibers,made from magnetic particles and the patient’s own blood,promises an immune-evading brain cancer therapy with minimal invasion.
文摘Traditional hybrid crop breeding faces inefficiencies due to labor-intensive manual pollination-especially for crops like tomatoes and soybeans with complex flowers.Researchers at the Institute of Genetics and Developmental Biology(IGDB),Chinese Academy of Sciences,have developed GEAIR(Genome Editing with Artificial-Intelligence-based Robots),an AI-robotic system that pollinates gene-edited plants 24/7.
基金supported by project RELIABLE(PTDC/EEI-AUT/3522/2020)R&D Unit SYSTEC-Base(UIDB001472020)+1 种基金Programmatic(UIDP001472020)funds-and Associate Laboratory Advanced Production and Intelligent Systems ARISE-LAP01122020funded by national funds through the FCT/MCTES(PIDDAC).
文摘The ability of mobile robots to plan and execute a path is foundational to various path-planning challenges,particularly Coverage Path Planning.While this task has been typically tackled with classical algorithms,these often struggle with flexibility and adaptability in unknown environments.On the other hand,recent advances in Reinforcement Learning offer promising approaches,yet a significant gap in the literature remains when it comes to generalization over a large number of parameters.This paper presents a unified,generalized framework for coverage path planning that leverages value-based deep reinforcement learning techniques.The novelty of the framework comes from the design of an observation space that accommodates different map sizes,an action masking scheme that guarantees safety and robustness while also serving as a learning-fromdemonstration technique during training,and a unique reward function that yields value functions that are size-invariant.These are coupled with a curriculum learning-based training strategy and parametric environment randomization,enabling the agent to tackle complete or partial coverage path planning with perfect or incomplete knowledge while generalizing to different map sizes,configurations,sensor payloads,and sub-tasks.Our empirical results show that the algorithm can perform zero-shot learning scenarios at a near-optimal level in environments that follow a similar distribution as during training,outperforming a greedy heuristic by sixfold.Furthermore,in out-of-distribution environments,our method surpasses existing state-of-the-art algorithms in most zero-shot and all few-shot scenarios,paving the way for generalizable and adaptable path-planning algorithms.
