The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability an...The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability and resource efficiency,particularly in mass customization scenarios where production schedules must accommodate dynamic and personalized demands.To address the challenges of dynamic task allocation,uncertainty,and realtime decision-making,this paper proposes Pathfinder,a deep reinforcement learning-based scheduling framework.Pathfinder models scheduling data through three key matrices:execution time(the time required for a job to complete),completion time(the actual time at which a job is finished),and efficiency(the performance of executing a single job).By leveraging neural networks,Pathfinder extracts essential features from these matrices,enabling intelligent decision-making in dynamic production environments.Unlike traditional approaches with fixed scheduling rules,Pathfinder dynamically selects from ten diverse scheduling rules,optimizing decisions based on real-time environmental conditions.To further enhance scheduling efficiency,a specialized reward function is designed to support dynamic task allocation and real-time adjustments.This function helps Pathfinder continuously refine its scheduling strategy,improving machine utilization and minimizing job completion times.Through reinforcement learning,Pathfinder adapts to evolving production demands,ensuring robust performance in real-world applications.Experimental results demonstrate that Pathfinder outperforms traditional scheduling approaches,offering improved coordination and efficiency in smart factories.By integrating deep reinforcement learning,adaptable scheduling strategies,and an innovative reward function,Pathfinder provides an effective solution to the growing challenges of multi-robot job scheduling in mass customization environments.展开更多
This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we id...This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we identify several avenues for enhancing existing methods.This survey describes some models of robots and commonly considered control objec-tives,followed by an in-depth analysis of four types of algo-rithms that can be employed for passing-through control:leader-follower formation control,multi-robot trajectory planning,con-trol-based methods,and virtual tube planning and control.Fur-thermore,we conduct a comparative analysis of these tech-niques and provide some subjective and general evaluations.展开更多
As a cross-cutting field between ocean development and multi-robot system(MRS),the underwater multi-robot system(UMRS)has gained increasing attention from researchers and engineers in recent decades.In this paper,we p...As a cross-cutting field between ocean development and multi-robot system(MRS),the underwater multi-robot system(UMRS)has gained increasing attention from researchers and engineers in recent decades.In this paper,we present a comprehensive survey of cooperation issues,one of the key components of UMRS,from the perspective of the emergence of new functions.More specifically,we categorize the cooperation in terms of task-space,motion-space,measurement-space,as well as their combination.Further,we analyze the architecture of UMRS from three aspects,i.e.,the performance of the individual underwater robot,the new functions of underwater robots,and the technical approaches of MRS.To conclude,we have discussed related promising directions for future research.This survey provides valuable insight into the reasonable utilization of UMRS to attain diverse underwater tasks in complex ocean application scenarios.展开更多
Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy sup...Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.展开更多
In unstructured environments, dynamic resource assignment is required for effective cooperation of robot teams. In some scenarios, robots are in charge of executing multiple missions simultaneously. This creates risks...In unstructured environments, dynamic resource assignment is required for effective cooperation of robot teams. In some scenarios, robots are in charge of executing multiple missions simultaneously. This creates risks of deadlock due to the presence of shared resources among various missions. The main contribution of this paper is the development of a novel approach that combines the one-step look-ahead deadlock avoidance policy with dynamic resource assignment. The dynamicresource assignment is achieved using greedy resource assignment for multi-mission robot teams in the framework of a matrix-based discrete event controller. Simulation results are presented in MATLAB to discuss in detail the proposed control strategy. The paper also discusses the toolkit developed in LabVIEW which is used to implement this control framework using a suitable example.展开更多
A new coordination scheme for multi-robot systems is proposed. A state space model of the multi- robot system is defined and constructed in which the system＇s initial and goal states are included along with the task ...A new coordination scheme for multi-robot systems is proposed. A state space model of the multi- robot system is defined and constructed in which the system＇s initial and goal states are included along with the task definition and the system＇s internal and external constraints. Task accomplishment is considered a transition of the system state in its state space （SS） under the system＇s constraints. Therefore, if there exists a connectable path within reachable area of the SS from the initial state to the goal state, the task is realizable. The optimal strategy for the task realization under constraints is investigated and reached by searching for the optimal state transition trajectory of the robot system in the SS. Moreover, if there is no connectable path, which means the task cannot be performed Successfully, the task could be transformed to be realizable by making the initial state and the goal state connectable and finding a path connecting them in the system＇s SS. This might be done via adjusting the system＇s configuration and/or task constraints. Experiments of multi-robot formation control with obstacles in the environment are conducted and simulation results show the validity of the proposed method.展开更多
This paper described a new method to plan out welding paths for multiple robots in virtual manufacturing environment. We first distribute welding tasks and priority for multi robots, and then apply corresponding behav...This paper described a new method to plan out welding paths for multiple robots in virtual manufacturing environment. We first distribute welding tasks and priority for multi robots, and then apply corresponding behavior rules to help to plan out welding paths for robots collision free, which is a base fixed problem. Finally, we testify the algorithm to be practical in virtual environment, and output robot programs to direct production process. This new way will help us to find a new development method for multiple robots path planning.展开更多
Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control prot...Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control protocols are devised via carefully designing a class of bounded artificial potential fields （APF） which could guarantee the connectivity maintenance, col ision avoidance and distance stabilization simultaneously during the system evolution. The connectivity of the underlying network can be preserved, and the desired stable flocking behavior can be achieved provided that the initial communication topology is strongly connected rather than undirected or balanced, which relaxes the constraints for group topology and extends the previous work to more generalized directed graphs. Furthermore, the proposed control algorithm is extended to solve the flocking problem with a virtual leader. In this case, it is shown that al robots can asymptotically move with the desired velocity and orientation even if there is only one informed robot in the team. Finally, nontrivial simulations and experiments are conducted to verify the effectiveness of the proposed algorithm.展开更多
A cooperative multi-robot system (CMRS) modeling method called fuzzy timed agent based Petri nets (FTAPN) is proposed in this paper, which has been extended from fuzzy timed object-oriented Petri net (FTOPN). The prop...A cooperative multi-robot system (CMRS) modeling method called fuzzy timed agent based Petri nets (FTAPN) is proposed in this paper, which has been extended from fuzzy timed object-oriented Petri net (FTOPN). The proposed FTAPN can be used to model and illustrate both the structural and dynamic aspects of CMRS, which is a typical multi-agent system (MAS). At the same time, supervised learning is supported in FTAPN. As a special type of high-level object, agent is introduced into FTAPN, which is used as a common modeling object in its model. The proposed FTAPN can not only be used to model CMRS and represent system aging effect, but also be refined into the object-oriented implementation easily. At the same time, it can also be regarded as a conceptual and practical artificial intelligence (AI) tool for multi-agent systems (MAS) into the mainstream practice of the software development.展开更多
In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a lar...In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a large workpiece is described as the MRSs with cooperation and antagonism interaction.By the signed graph theory,it is further transformed into a bipartite consensus control problem,where all followers are uniformly degenerated into the general nonlinear systems based on the lateral error model.To augment the flexibility of control protocol and improve control performance,a higher-dimensional full form dynamic linearization(FFDL)technique is committed to the MRSs.The control input criterion function consists of the data model based on FFDL and the bipartite consensus error based on the signed graph theory,and the proposed control protocol is given by optimizing this criterion function.In this way,this scheme has a higher degree of freedom and better adaptive adjustment capability while not excessively increasing the control method complexity,and it can also be compatible with other forms of dynamic linearization techniques in MRSs.Further,three matrix norm lemmas are introduced to deal with the challenges of stability analysis caused by higher matrix dimensions and more robots.Finally,the effectiveness of the proposed method is verified by numerical simulations.展开更多
Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for...Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.展开更多
Malignant pleural effusion(MPE) is a serious disease caused by malignant tumors with high morbidity and mortality.Chemotherapy,immunotherapy,and antiangiogenic therapy are common treatments for MPE at present.However,...Malignant pleural effusion(MPE) is a serious disease caused by malignant tumors with high morbidity and mortality.Chemotherapy,immunotherapy,and antiangiogenic therapy are common treatments for MPE at present.However,traditional chemotherapeutic drugs have many side effects and can easily lead to drug resistance in patients.The complex tumor microenvironment(TME) of MPE directly reduces the antitumor efficacy of immunotherapy.Fortunately,drug delivery systems(DDSs) based on biomaterials have the ability to overcome some of the drawbacks of conventional treatments by improving drug stability,increasing the accuracy of tumor cell targeting,reducing toxic side effects,and remodeling TME,ultimately improving drug efficacy.Therefore,the purpose of this review is to provide an overview and discussion of the latest progress in biomaterial-based DDSs for the treatment of MPE.We discuss the application of biomaterials in the treatment of MPE from multiple perspectives,including chemotherapy,immunotherapy,combination therapy,and pleurodesis,where microspheres,cell membrane-derived microparticles(MPs),micelles,nanoparticles,and liposomes,are involved.The application of these biomaterials has been proven to have great potential in the treatment of MPE,providing a new idea for follow-up research.展开更多
Reliable detection of traffic signs and lights(TSLs)at long range and under varying illumination is essen-tial for improving the perception and safety of autonomous driving systems(ADS).Traditional object detection mo...Reliable detection of traffic signs and lights(TSLs)at long range and under varying illumination is essen-tial for improving the perception and safety of autonomous driving systems(ADS).Traditional object detection models often exhibit significant performance degradation in real-world environments characterized by high dynamic range and complex lighting conditions.To overcome these limitations,this research presents FED-YOLOv10s,an improved and lightweight object detection framework based on You Only look Once v10(YOLOv10).The proposed model integrates a C2f-Faster block derived from FasterNet to reduce parameters and floating-point operations,an Efficient Multiscale Attention(EMA)mechanism to improve TSL-invariant feature extraction,and a deformable Convolution Networks v4(DCNv4)module to enhance multiscale spatial adaptability.Experimental findings demonstrate that the proposed architecture achieves an optimal balance between computational efficiency and detection accuracy,attaining an F1-score of 91.8%,and mAP@0.5 of 95.1%,while reducing parameters to 8.13 million.Comparative analyses across multiple traffic sign detection benchmarks demonstrate that FED-YOLOv10s outperforms state-of-the-art models in precision,recall,and mAP.These results highlight FED-YOLOv10s as a robust,efficient,and deployable solution for intelligent traffic perception in ADS.展开更多
Each morning at Yangluo Port in Wuhan,Hubei Province,the all-electric cargo vessel Huahang Xinneng No.1 completes a battery swap in under 10 minutes before returning to service with nearly 8,000 kWh of power onboard。
Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive exa...Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.展开更多
Hydrogen,as a zero-carbon secondary energy carrier,provides a unified pathway for low-carbon energy transformation.In electro–hydrogen coupling systems(EHCSs),surplus renewable power is stored via water electrolysis ...Hydrogen,as a zero-carbon secondary energy carrier,provides a unified pathway for low-carbon energy transformation.In electro–hydrogen coupling systems(EHCSs),surplus renewable power is stored via water electrolysis and later reconverted to electricity using fuel cells or gas turbines,enhancing the system’s flexibility and reliability in support of deep decarbonization.This study constructs an electricity–hydrogen energy-recycling model based on a coupling relationship considering the bidirectional conversion between electricity and hydrogen.A multistage carbon-emission-reduction indicator constraint is also established.Additionally,the green-certificate and carbon trading markets are introduced to optimize equipment investment and operation costs while achieving carbon-emission reduction.A case study reveals that the proposed EHCS planning model effectively allocates carbon emissions across different system stages,while mitigating economic repercussions,thus ensuring closer alignment with China’s emission-reduction policies.Incorporating diverse market mechanisms significantly enhances the system’s economy and decision-making flexibility,particularly in addressing future challenges in the energy market.展开更多
The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can...The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.展开更多
This paper studies the problem of formation-containment for multi-robot systems with stochastic sampling.First,a stochastic sampling control protocol is proposed,in which information exchanging among robots only occur...This paper studies the problem of formation-containment for multi-robot systems with stochastic sampling.First,a stochastic sampling control protocol is proposed,in which information exchanging among robots only occurred at the sampling time and two different sampling periods randomly switch.Thus,both energy and controller updating frequencies can be reduced.Also,the protocol can be applied to the situation where the sampling period varies stochastically.Second,sufficient conditions guaranteeing mean square formation-containment are derived.Under stochastic sampling mechanism,the leaders reach a geometric formation shape and the followers are in the geometric formation shape formed by the leaders.Finally,an example is shown to demonstrate the results.展开更多
With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenu...With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.展开更多
Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportatio...Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportation systems (ITS) and Advanced Driver Assistance Systems (ADAS), the development of efficient and reliable traffic light detection mechanisms is crucial for enhancing road safety and traffic management. This paper presents an optimized convolutional neural network (CNN) framework designed to detect traffic lights in real-time within complex urban environments. Leveraging multi-scale pyramid feature maps, the proposed model addresses key challenges such as the detection of small, occluded, and low-resolution traffic lights amidst complex backgrounds. The integration of dilated convolutions, Region of Interest (ROI) alignment, and Soft Non-Maximum Suppression (Soft-NMS) further improves detection accuracy and reduces false positives. By optimizing computational efficiency and parameter complexity, the framework is designed to operate seamlessly on embedded systems, ensuring robust performance in real-world applications. Extensive experiments using real-world datasets demonstrate that our model significantly outperforms existing methods, providing a scalable solution for ITS and ADAS applications. This research contributes to the advancement of Artificial Intelligence-driven (AI-driven) pattern recognition in transportation systems and offers a mathematical approach to improving efficiency and safety in logistics and transportation networks.展开更多
基金supported by National Natural Science Foundation of China under Grant No.62372110Fujian Provincial Natural Science of Foundation under Grants 2023J02008,2024H0009.
文摘The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability and resource efficiency,particularly in mass customization scenarios where production schedules must accommodate dynamic and personalized demands.To address the challenges of dynamic task allocation,uncertainty,and realtime decision-making,this paper proposes Pathfinder,a deep reinforcement learning-based scheduling framework.Pathfinder models scheduling data through three key matrices:execution time(the time required for a job to complete),completion time(the actual time at which a job is finished),and efficiency(the performance of executing a single job).By leveraging neural networks,Pathfinder extracts essential features from these matrices,enabling intelligent decision-making in dynamic production environments.Unlike traditional approaches with fixed scheduling rules,Pathfinder dynamically selects from ten diverse scheduling rules,optimizing decisions based on real-time environmental conditions.To further enhance scheduling efficiency,a specialized reward function is designed to support dynamic task allocation and real-time adjustments.This function helps Pathfinder continuously refine its scheduling strategy,improving machine utilization and minimizing job completion times.Through reinforcement learning,Pathfinder adapts to evolving production demands,ensuring robust performance in real-world applications.Experimental results demonstrate that Pathfinder outperforms traditional scheduling approaches,offering improved coordination and efficiency in smart factories.By integrating deep reinforcement learning,adaptable scheduling strategies,and an innovative reward function,Pathfinder provides an effective solution to the growing challenges of multi-robot job scheduling in mass customization environments.
文摘This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we identify several avenues for enhancing existing methods.This survey describes some models of robots and commonly considered control objec-tives,followed by an in-depth analysis of four types of algo-rithms that can be employed for passing-through control:leader-follower formation control,multi-robot trajectory planning,con-trol-based methods,and virtual tube planning and control.Fur-thermore,we conduct a comparative analysis of these tech-niques and provide some subjective and general evaluations.
基金This work was supported in part by the National Natural Science Foundation of China(U1909206,61725305,61903007,62073196)in part by the S&T Program of Hebei(F2020203037).
文摘As a cross-cutting field between ocean development and multi-robot system(MRS),the underwater multi-robot system(UMRS)has gained increasing attention from researchers and engineers in recent decades.In this paper,we present a comprehensive survey of cooperation issues,one of the key components of UMRS,from the perspective of the emergence of new functions.More specifically,we categorize the cooperation in terms of task-space,motion-space,measurement-space,as well as their combination.Further,we analyze the architecture of UMRS from three aspects,i.e.,the performance of the individual underwater robot,the new functions of underwater robots,and the technical approaches of MRS.To conclude,we have discussed related promising directions for future research.This survey provides valuable insight into the reasonable utilization of UMRS to attain diverse underwater tasks in complex ocean application scenarios.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2015AA015403)the National Natural Science Foundation of China(61404069,61401185)the Project of Education Department of Liaoning Province(LJYL052)
文摘Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.
基金supported by the Army Research Office(ARO)(DAAD 19-02-1-0366,ARO W91NF-05-1-0314)the National Science Foundation(IIS-0326505,CNS-0421282)+1 种基金the Singapore SERC TSRP(0421120028)the NI Lead User grant,and the Texas Advanced Research Program(ARP)(14-748779)
文摘In unstructured environments, dynamic resource assignment is required for effective cooperation of robot teams. In some scenarios, robots are in charge of executing multiple missions simultaneously. This creates risks of deadlock due to the presence of shared resources among various missions. The main contribution of this paper is the development of a novel approach that combines the one-step look-ahead deadlock avoidance policy with dynamic resource assignment. The dynamicresource assignment is achieved using greedy resource assignment for multi-mission robot teams in the framework of a matrix-based discrete event controller. Simulation results are presented in MATLAB to discuss in detail the proposed control strategy. The paper also discusses the toolkit developed in LabVIEW which is used to implement this control framework using a suitable example.
基金the National Natural Science Foundation of China (60428303).
文摘A new coordination scheme for multi-robot systems is proposed. A state space model of the multi- robot system is defined and constructed in which the system＇s initial and goal states are included along with the task definition and the system＇s internal and external constraints. Task accomplishment is considered a transition of the system state in its state space （SS） under the system＇s constraints. Therefore, if there exists a connectable path within reachable area of the SS from the initial state to the goal state, the task is realizable. The optimal strategy for the task realization under constraints is investigated and reached by searching for the optimal state transition trajectory of the robot system in the SS. Moreover, if there is no connectable path, which means the task cannot be performed Successfully, the task could be transformed to be realizable by making the initial state and the goal state connectable and finding a path connecting them in the system＇s SS. This might be done via adjusting the system＇s configuration and/or task constraints. Experiments of multi-robot formation control with obstacles in the environment are conducted and simulation results show the validity of the proposed method.
基金Natural Science Foundation of China (No.5 98895 0 5 )
文摘This paper described a new method to plan out welding paths for multiple robots in virtual manufacturing environment. We first distribute welding tasks and priority for multi robots, and then apply corresponding behavior rules to help to plan out welding paths for robots collision free, which is a base fixed problem. Finally, we testify the algorithm to be practical in virtual environment, and output robot programs to direct production process. This new way will help us to find a new development method for multiple robots path planning.
基金supported by the National Natural Science Foundation of China(61175112)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(G61321002)+3 种基金the Projects of Major International(Regional)Joint Research Program(61120106010)the Beijing Education Committee Cooperation Building Foundationthe Program for Changjiang Scholars and Innovative Research Team in University(IRT1208)the ChangJiang Scholars Program and the Beijing Outstanding Ph.D.Program Mentor Grant(20131000704)
文摘Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control protocols are devised via carefully designing a class of bounded artificial potential fields （APF） which could guarantee the connectivity maintenance, col ision avoidance and distance stabilization simultaneously during the system evolution. The connectivity of the underlying network can be preserved, and the desired stable flocking behavior can be achieved provided that the initial communication topology is strongly connected rather than undirected or balanced, which relaxes the constraints for group topology and extends the previous work to more generalized directed graphs. Furthermore, the proposed control algorithm is extended to solve the flocking problem with a virtual leader. In this case, it is shown that al robots can asymptotically move with the desired velocity and orientation even if there is only one informed robot in the team. Finally, nontrivial simulations and experiments are conducted to verify the effectiveness of the proposed algorithm.
文摘A cooperative multi-robot system (CMRS) modeling method called fuzzy timed agent based Petri nets (FTAPN) is proposed in this paper, which has been extended from fuzzy timed object-oriented Petri net (FTOPN). The proposed FTAPN can be used to model and illustrate both the structural and dynamic aspects of CMRS, which is a typical multi-agent system (MAS). At the same time, supervised learning is supported in FTAPN. As a special type of high-level object, agent is introduced into FTAPN, which is used as a common modeling object in its model. The proposed FTAPN can not only be used to model CMRS and represent system aging effect, but also be refined into the object-oriented implementation easily. At the same time, it can also be regarded as a conceptual and practical artificial intelligence (AI) tool for multi-agent systems (MAS) into the mainstream practice of the software development.
基金supported in part by the National Natural Science Foundation of China(62473142,62203161)Special Funding Support for the Construction of Innovative Provinces in Hunan Province(2021GK1010)+1 种基金Guangdong Basic and Applied Basic Research Foundation(2024A1515011579),Project of State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle(72275007).
文摘In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a large workpiece is described as the MRSs with cooperation and antagonism interaction.By the signed graph theory,it is further transformed into a bipartite consensus control problem,where all followers are uniformly degenerated into the general nonlinear systems based on the lateral error model.To augment the flexibility of control protocol and improve control performance,a higher-dimensional full form dynamic linearization(FFDL)technique is committed to the MRSs.The control input criterion function consists of the data model based on FFDL and the bipartite consensus error based on the signed graph theory,and the proposed control protocol is given by optimizing this criterion function.In this way,this scheme has a higher degree of freedom and better adaptive adjustment capability while not excessively increasing the control method complexity,and it can also be compatible with other forms of dynamic linearization techniques in MRSs.Further,three matrix norm lemmas are introduced to deal with the challenges of stability analysis caused by higher matrix dimensions and more robots.Finally,the effectiveness of the proposed method is verified by numerical simulations.
基金support from the Contract Research(“Development of Breathable Fabrics with Nano-Electrospun Membrane”,CityU ref.:9231419“Research and application of antibacterial and healing-promoting smart nanofiber dressing for children’s burn wounds”,CityU ref:PJ9240111)+1 种基金the National Natural Science Foundation of China(“Study of Multi-Responsive Shape Memory Polyurethane Nanocomposites Inspired by Natural Fibers”,Grant No.51673162)Startup Grant of CityU(“Laboratory of Wearable Materials for Healthcare”,Grant No.9380116).
文摘Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.
基金financial support from the Noncommunicable Chronic Diseases-National Science and Technology Major Project (Nos.2024ZD0522800,2024ZD0522803)the National Natural Science Foundation of China (Nos.U21A20417,31930067,31800797)+2 种基金the Natural Science Foundation of Sichuan Province (No.2024NSFSC0046)the Sichuan Science and Technology Program (No.2022YFS0333)the 1·3·5 Project for Disciplines of Excellence,West China Hospital,Sichuan University (No.ZYGD24003)。
文摘Malignant pleural effusion(MPE) is a serious disease caused by malignant tumors with high morbidity and mortality.Chemotherapy,immunotherapy,and antiangiogenic therapy are common treatments for MPE at present.However,traditional chemotherapeutic drugs have many side effects and can easily lead to drug resistance in patients.The complex tumor microenvironment(TME) of MPE directly reduces the antitumor efficacy of immunotherapy.Fortunately,drug delivery systems(DDSs) based on biomaterials have the ability to overcome some of the drawbacks of conventional treatments by improving drug stability,increasing the accuracy of tumor cell targeting,reducing toxic side effects,and remodeling TME,ultimately improving drug efficacy.Therefore,the purpose of this review is to provide an overview and discussion of the latest progress in biomaterial-based DDSs for the treatment of MPE.We discuss the application of biomaterials in the treatment of MPE from multiple perspectives,including chemotherapy,immunotherapy,combination therapy,and pleurodesis,where microspheres,cell membrane-derived microparticles(MPs),micelles,nanoparticles,and liposomes,are involved.The application of these biomaterials has been proven to have great potential in the treatment of MPE,providing a new idea for follow-up research.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia under Grant No.IPP:172-830-2025.
文摘Reliable detection of traffic signs and lights(TSLs)at long range and under varying illumination is essen-tial for improving the perception and safety of autonomous driving systems(ADS).Traditional object detection models often exhibit significant performance degradation in real-world environments characterized by high dynamic range and complex lighting conditions.To overcome these limitations,this research presents FED-YOLOv10s,an improved and lightweight object detection framework based on You Only look Once v10(YOLOv10).The proposed model integrates a C2f-Faster block derived from FasterNet to reduce parameters and floating-point operations,an Efficient Multiscale Attention(EMA)mechanism to improve TSL-invariant feature extraction,and a deformable Convolution Networks v4(DCNv4)module to enhance multiscale spatial adaptability.Experimental findings demonstrate that the proposed architecture achieves an optimal balance between computational efficiency and detection accuracy,attaining an F1-score of 91.8%,and mAP@0.5 of 95.1%,while reducing parameters to 8.13 million.Comparative analyses across multiple traffic sign detection benchmarks demonstrate that FED-YOLOv10s outperforms state-of-the-art models in precision,recall,and mAP.These results highlight FED-YOLOv10s as a robust,efficient,and deployable solution for intelligent traffic perception in ADS.
文摘Each morning at Yangluo Port in Wuhan,Hubei Province,the all-electric cargo vessel Huahang Xinneng No.1 completes a battery swap in under 10 minutes before returning to service with nearly 8,000 kWh of power onboard。
文摘Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.
基金supported by State Grid Jiangsu Electric Power Co.,Ltd.Technology Project(Research on Planning and Operation Technology of Electric–Hydrogen Coupling System Driven by the Electric–Carbon–Green Certificate Market):J2024005.
文摘Hydrogen,as a zero-carbon secondary energy carrier,provides a unified pathway for low-carbon energy transformation.In electro–hydrogen coupling systems(EHCSs),surplus renewable power is stored via water electrolysis and later reconverted to electricity using fuel cells or gas turbines,enhancing the system’s flexibility and reliability in support of deep decarbonization.This study constructs an electricity–hydrogen energy-recycling model based on a coupling relationship considering the bidirectional conversion between electricity and hydrogen.A multistage carbon-emission-reduction indicator constraint is also established.Additionally,the green-certificate and carbon trading markets are introduced to optimize equipment investment and operation costs while achieving carbon-emission reduction.A case study reveals that the proposed EHCS planning model effectively allocates carbon emissions across different system stages,while mitigating economic repercussions,thus ensuring closer alignment with China’s emission-reduction policies.Incorporating diverse market mechanisms significantly enhances the system’s economy and decision-making flexibility,particularly in addressing future challenges in the energy market.
基金Hongguang Wu,Both authors contributed equally to this work and share first authorshipLing Dong,Both authors contributed equally to this work and share first authorship。
文摘The human retina,a complex and highly specialized structure,includes multiple cell types that work synergistically to generate and transmit visual signals.However,genetic predisposition or age-related degeneration can lead to retinal damage that severely impairs vision or causes blindness.Treatment options for retinal diseases are limited,and there is an urgent need for innovative therapeutic strategies.Cell and gene therapies are promising because of the efficacy of delivery systems that transport therapeutic genes to targeted retinal cells.Gene delivery systems hold great promise for treating retinal diseases by enabling the targeted delivery of therapeutic genes to affected cells or by converting endogenous cells into functional ones to facilitate nerve regeneration,potentially restoring vision.This review focuses on two principal categories of gene delivery vectors used in the treatment of retinal diseases:viral and non-viral systems.Viral vectors,including lentiviruses and adeno-associated viruses,exploit the innate ability of viruses to infiltrate cells,which is followed by the introduction of therapeutic genetic material into target cells for gene correction.Lentiviruses can accommodate exogenous genes up to 8 kb in length,but their mechanism of integration into the host genome presents insertion mutation risks.Conversely,adeno-associated viruses are safer,as they exist as episomes in the nucleus,yet their limited packaging capacity constrains their application to a narrower spectrum of diseases,which necessitates the exploration of alternative delivery methods.In parallel,progress has also occurred in the development of novel non-viral delivery systems,particularly those based on liposomal technology.Manipulation of the ratios of hydrophilic and hydrophobic molecules within liposomes and the development of new lipid formulations have led to the creation of advanced non-viral vectors.These innovative systems include solid lipid nanoparticles,polymer nanoparticles,dendrimers,polymeric micelles,and polymeric nanoparticles.Compared with their viral counterparts,non-viral delivery systems offer markedly enhanced loading capacities that enable the direct delivery of nucleic acids,mRNA,or protein molecules into cells.This bypasses the need for DNA transcription and processing,which significantly enhances therapeutic efficiency.Nevertheless,the immunogenic potential and accumulation toxicity associated with non-viral particulate systems necessitates continued optimization to reduce adverse effects in vivo.This review explores the various delivery systems for retinal therapies and retinal nerve regeneration,and details the characteristics,advantages,limitations,and clinical applications of each vector type.By systematically outlining these factors,our goal is to guide the selection of the optimal delivery tool for a specific retinal disease,which will enhance treatment efficacy and improve patient outcomes while paving the way for more effective and targeted therapeutic interventions.
基金supported by the National Natural Science Foundation of China(Grant No.61873318)the Frontier Research Funds of Applied Foundation of Wuhan(Grant No.2019010701011421)+1 种基金the National Defense Scienceof China(Grant No.JCKY2017207B005)the Program for HUST(Huazhong University of Science and Technology)Academic Frontier Youth Team(Grant No.2018QYTD07)。
文摘This paper studies the problem of formation-containment for multi-robot systems with stochastic sampling.First,a stochastic sampling control protocol is proposed,in which information exchanging among robots only occurred at the sampling time and two different sampling periods randomly switch.Thus,both energy and controller updating frequencies can be reduced.Also,the protocol can be applied to the situation where the sampling period varies stochastically.Second,sufficient conditions guaranteeing mean square formation-containment are derived.Under stochastic sampling mechanism,the leaders reach a geometric formation shape and the followers are in the geometric formation shape formed by the leaders.Finally,an example is shown to demonstrate the results.
基金Supported by Beijing Municipal Natural Science Foundation of China(Grant No.24JL002)China Postdoctoral Science Foundation(Grant No.2024M754054)+2 种基金National Natural Science Foundation of China(Grant No.52120105008)Beijing Municipal Outstanding Young Scientis Program of Chinathe New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.
基金funded by the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia through research group No.(RG-NBU-2022-1234).
文摘Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportation systems (ITS) and Advanced Driver Assistance Systems (ADAS), the development of efficient and reliable traffic light detection mechanisms is crucial for enhancing road safety and traffic management. This paper presents an optimized convolutional neural network (CNN) framework designed to detect traffic lights in real-time within complex urban environments. Leveraging multi-scale pyramid feature maps, the proposed model addresses key challenges such as the detection of small, occluded, and low-resolution traffic lights amidst complex backgrounds. The integration of dilated convolutions, Region of Interest (ROI) alignment, and Soft Non-Maximum Suppression (Soft-NMS) further improves detection accuracy and reduces false positives. By optimizing computational efficiency and parameter complexity, the framework is designed to operate seamlessly on embedded systems, ensuring robust performance in real-world applications. Extensive experiments using real-world datasets demonstrate that our model significantly outperforms existing methods, providing a scalable solution for ITS and ADAS applications. This research contributes to the advancement of Artificial Intelligence-driven (AI-driven) pattern recognition in transportation systems and offers a mathematical approach to improving efficiency and safety in logistics and transportation networks.
