The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversari...The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.展开更多
Reconfigurable intelligent surface(RIS)has proven to be promising for future wireless communication.Due to its ability to manipulate electromagnetic(EM)waves,RIS provides a flexible and programmable way to implement i...Reconfigurable intelligent surface(RIS)has proven to be promising for future wireless communication.Due to its ability to manipulate electromagnetic(EM)waves,RIS provides a flexible and programmable way to implement intelligent wireless environments.While path loss modeling has been conducted in some prior research,an issue remaining unknown is the characteristics of multi-beam path loss for RIS.In this paper,we model,simulate and measure the multi-beam path loss in RIS-assisted broadcast communication scenarios.We propose two specific configurations of RIS and derive the path loss models,which reveal that the incident beam can be equally divided into multiple beams without power loss through rational design of the phase coding.The proposed path loss model is validated through simulation subsequently.To further verify our conclusions,we build a millimeter wave(mmWave)measurement system with a 35 GHz fabricated RIS.The measurement result corresponds well with the simulation,which shows a difference of about 3 dB in the received signal power of quad-beam compared with dual-beam,as well as dual-beam compared with single-beam,except for the impact of radiation patterns of the antennas and RIS elements.展开更多
Solving the path planning problem of Autonomous Underwater Vehicles(AUVs)is crucial for reducing energy waste and improving operational efficiency.However,two main challenges hinder further development:Firstly,existin...Solving the path planning problem of Autonomous Underwater Vehicles(AUVs)is crucial for reducing energy waste and improving operational efficiency.However,two main challenges hinder further development:Firstly,existing algorithms often treat this as a single-objective optimization problem,whereas in reality,it should be multi-objective,considering factors such as distance,safety,and smoothness simultaneously.Secondly,the limited availability of optimization results arises due to they are single-path,which fail to meet real-world conditions.To address these challenges,first of all,an improved AUV path planning model is proposed,in which the collisions of path and obstacles are classified more specifically.Subsequently,a novel Altruistic Nurturing Algorithm(ANA)inspired by natural altruism is introduced.In the algorithm,nurturing cost considering Pareto rank and crowd distance is introduced as guidance of evolution to avoid futile calculation,abandonment threshold is self-adaptive with descendant situation to help individuals escape from local optima and double selection strategy combining crowd and k-nearest neighbors selection helps to get a better-distributed Pareto front.Experimental results comparing ANA with existing algorithms in AUV path planning demonstrate its superiority.Finally,a user-friendly interface,the Multi-Objective AUV Path Planner,is designed to provide users with a group of paths for informed decisionmaking.展开更多
An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorith...An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorithms.This algorithm considers factors such as initial position and orientation of the ship,safety range,and ship draft to determine the optimal obstacle-avoiding route from the current to the destination point for ship planning.A coordinate transformation algorithm is also applied to convert commonly used latitude and longitude coordinates of ship travel paths to easily utilized and analyzed Cartesian coordinates.The algorithm incorporates a hierarchical chart processing algorithm to handle multilayered chart data.Furthermore,the algorithm considers the impact of ship length on grid size and density when implementing chart gridification,adjusting the grid size and density accordingly based on ship length.Simulation results show that compared to traditional path planning algorithms,the sparse A^(*)algorithm reduces the average number of path points by 25%,decreases the average maximum storage node number by 17%,and raises the average path turning angle by approximately 10°,effectively improving the safety of ship planning paths.展开更多
The traditional A^(*)algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,wh...The traditional A^(*)algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,which is not conducive to the control of USV and also affects navigation safety.In this paper,these problems were addressed through the following improvements.First,the path search angle and security were comprehensively considered,and a security expansion strategy of nodes based on the 5×5 neighborhood was proposed.The A^(*)algorithm search neighborhood was expanded from 3×3 to 5×5,and safe nodes were screened out for extension via the node security expansion strategy.This algorithm can also optimize path search angles while improving path security.Second,the distance from the current node to the target node was introduced into the heuristic function.The efficiency of the A^(*)algorithm was improved,and the path was smoothed using the Floyd algorithm.For the dynamic adjustment of the weight to improve the efficiency of DWA,the distance from the USV to the target point was introduced into the evaluation function of the dynamic-window approach(DWA)algorithm.Finally,combined with the local target point selection strategy,the optimized DWA algorithm was performed for local path planning.The experimental results show the smooth and safe path planned by the fusion algorithm,which can successfully avoid dynamic obstacles and is effective and feasible in path planning for USVs.展开更多
The Wiener index of a graph is defined to be the sum of the distances of all pairs of vertices in the graph.The kth power G^(k) of a graph G is the graph on V(G)and two vertices are adjacent if and only if their dista...The Wiener index of a graph is defined to be the sum of the distances of all pairs of vertices in the graph.The kth power G^(k) of a graph G is the graph on V(G)and two vertices are adjacent if and only if their distance in G is less or equal to k.In this paper,we computed the Wiener index of the kth power of paths and cycles for any k≥2.展开更多
Path planning for recovery is studied on the engineering background of double unmanned surface vehicles(USVs)towing oil booms for oil spill recovery.Given the influence of obstacles on the sea,the improved artificial ...Path planning for recovery is studied on the engineering background of double unmanned surface vehicles(USVs)towing oil booms for oil spill recovery.Given the influence of obstacles on the sea,the improved artificial potential field(APF)method is used for path planning.For addressing the two problems of unreachable target and local minimum in the APF,three improved algorithms are proposed by combining the motion performance constraints of the double USV system.These algorithms are then combined as the final APF-123 algorithm for oil spill recovery.Multiple sets of simulation tests are designed according to the flaws of the APF and the process of oil spill recovery.Results show that the proposed algorithms can ensure the system’s safety in tracking oil spills in a complex environment,and the speed is increased by more than 40%compared with the APF method.展开更多
Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV...Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.展开更多
Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a gro...Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.展开更多
Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical ...Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.展开更多
This paper focuses on optimally determining the existence of connected paths between some given nodes in random ring-based graphs.Serving as a fundamental underlying structure in network modeling,ring topology appears...This paper focuses on optimally determining the existence of connected paths between some given nodes in random ring-based graphs.Serving as a fundamental underlying structure in network modeling,ring topology appears as commonplace in many realistic scenarios.Regarding this,we consider graphs composed of rings,with some possible connected paths between them.Without prior knowledge of the exact node permutations on rings,the existence of each edge can be unraveled through edge testing at a unit cost in one step.The problem examined is that of determining whether the given nodes are connected by a path or separated by a cut,with the minimum expected costs involved.Dividing the problem into different cases based on different topologies of the ring-based networks,we propose the corresponding policies that aim to quickly seek the paths between nodes.A common feature shared by all those policies is that we stick to going in the same direction during edge searching,with edge testing in each step only involving the test between the source and the node that has been tested most.The simple searching rule,interestingly,can be interpreted as a delightful property stemming from the neat structure of ring-based networks,which makes the searching process not rely on any sophisticated behaviors.We prove the optimality of the proposed policies by calculating the expected cost incurred and making a comparison with the other class of strategies.The effectiveness of the proposed policies is also verified through extensive simulations,from which we even disclose three extra intriguing findings:i)in a onering network,the cost will grow drastically with the number of designated nodes when the number is small and will grow slightly when that number is large;ii)in ring-based network,Depth First is optimal in detecting the connectivity between designated nodes;iii)the problem of multi-ring networks shares large similarity with that of two-ring networks,and a larger number of ties between rings will not influence the expected cost.展开更多
This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the fe...This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.展开更多
Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE...Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.展开更多
With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated...With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.展开更多
Both bulk stress(σ_(i i))and stress path(SP)significantly affect the transportation characteristics of deep gas during reservoir pressure depletion.Therefore,the experimental study of horizontal stress unloading on s...Both bulk stress(σ_(i i))and stress path(SP)significantly affect the transportation characteristics of deep gas during reservoir pressure depletion.Therefore,the experimental study of horizontal stress unloading on seepage behavior of gas-bearing coal under constantσi i-constraints is performed.The results show that coal permeability is affected by horizontal stress anisotropy(σ_(H)≠σh),and the contribution of minor horizontal stress to permeability is related to the differential response of horizontal strain.The slippage phenomenon is prominent in deep high-stress regime,especially in low reservoir pressure.σ_(i i)and SP jointly determine the manifestation of slippage effect and the strength of stress sensitivity(γ)of permeability.Deep reservoir implies an incremental percentage of slip-based permeability,and SP weakens the slippage effect by changing the elastic–plastic state of coal.However,γis negatively correlated with slippage effect.From the Walsh model,narrow(low aspect-ratio)fractures within the coal under unloading SP became the main channel for gas seepage,and bring the effective stress coefficient of permeability(χ)less than 1 for both low-stress elastic and high-stress damaged coal.With the raise of the effective stress,the effect of pore-lined clay particles on permeability was enhanced,inducing an increase inχfor highstress elastic coal.展开更多
This paper addresses the estimation problem of an unknown drift parameter matrix for a fractional Ornstein-Uhlenbeck process in a multi-dimensional setting.To tackle this problem,we propose a novel approach based on r...This paper addresses the estimation problem of an unknown drift parameter matrix for a fractional Ornstein-Uhlenbeck process in a multi-dimensional setting.To tackle this problem,we propose a novel approach based on rough path theory that allows us to construct pathwise rough path estimators from both continuous and discrete observations of a single path.Our approach is particularly suitable for high-frequency data.To formulate the parameter estimators,we introduce a theory of pathwise Itôintegrals with respect to fractional Brownian motion.By establishing the regularity of fractional Ornstein-Uhlenbeck processes and analyzing the long-term behavior of the associated Lévy area processes,we demonstrate that our estimators are strongly consistent and pathwise stable.Our findings offer a new perspective on estimating the drift parameter matrix for fractional Ornstein-Uhlenbeck processes in multi-dimensional settings,and may have practical implications for fields including finance,economics,and engineering.展开更多
This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapi...This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.展开更多
CO_(2) conversion into value-added products by electro-, photoand plasma catalysis under mild operating conditions(ambient temperature and pressure) is an emerging area to achieve carbon circularity by producing chemi...CO_(2) conversion into value-added products by electro-, photoand plasma catalysis under mild operating conditions(ambient temperature and pressure) is an emerging area to achieve carbon circularity by producing chemicals and fuels using directly renewable energy. Among all CO_(2) conversion approaches, the electrocatalytic reduction of CO_(2) is the most mature technology, capable of achieving high productivity(i.e. high current densities) at large scale, especially for producing carbon monoxide(CO), but with many examples showing selectivity to C_(2) carbon products.展开更多
The path-following control design for an autonomous underwater vehicle(AUV)requires prior full or partial knowledge about the mathematical model defined through Newton’s second law based on a geometrical investigatio...The path-following control design for an autonomous underwater vehicle(AUV)requires prior full or partial knowledge about the mathematical model defined through Newton’s second law based on a geometrical investigation.AUV dynamics are highly nonlinear and time-varying,facing unpredictable disturbances due to AUVs operating in deep,hazardous oceanic environments.Consequently,navigation guidance and control systems for AUVs must learn and adapt to the time-varying dynamics of the nonlinear fully coupled vehicle model in the presence of highly unstructured underwater operating conditions.Many control engineers focus on the application of robust model-free adaptive control techniques in AUV maneuvers.Hence,the main goal is to design a novel salp swarm optimization of super twisting algorithm-based secondorder sliding mode controller for the planar path-following control of an AUV through regulation of the heading angle parameter.The finite time for tracking error convergence in the horizontal plane is provided through the control structure architecture,particularly for lateral deviations from the desired path.The proposed control law is designed such that it steers a robotic vehicle to track a predefined planar path at a constant speed determined by an end-user,without any temporal specification.Finally,the efficacy and tracking accuracy are evaluated through comparative analysis based on simulation and experimental hardware-in-loop assessment without violating the input constraints.Moreover,the proposed control law can handle parametric uncertainties and unpredictable disturbances such as ocean currents,wind,and measurement noise.展开更多
基金supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2020MA092)the Innovation Project for Graduate Students of Ludong University(Grant No.IPGS2024-048).
文摘The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.
基金supported in part by the National Key Research and Development Program of China under Grants 2023YFB3811505in part by the National Natural Science Foundation of China(NSFC)under Grants 62261160576,62201138,62301156,and 62401137+4 种基金in part by the Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry)under Grants BE2023022-1 and BE2023022in part by the Natural Science Foundation of Jiangsu Province under Grant BK20220809 and BK20241281in part by the Fundamental Research Funds for the Central Universities under Grant 2242023K5003in part by the China National Postdoctoral Program for Innovative Talents under Grant BX20230065in part by the Jiangsu Excellent Postdoctoral Program under Grant 2023ZB476.
文摘Reconfigurable intelligent surface(RIS)has proven to be promising for future wireless communication.Due to its ability to manipulate electromagnetic(EM)waves,RIS provides a flexible and programmable way to implement intelligent wireless environments.While path loss modeling has been conducted in some prior research,an issue remaining unknown is the characteristics of multi-beam path loss for RIS.In this paper,we model,simulate and measure the multi-beam path loss in RIS-assisted broadcast communication scenarios.We propose two specific configurations of RIS and derive the path loss models,which reveal that the incident beam can be equally divided into multiple beams without power loss through rational design of the phase coding.The proposed path loss model is validated through simulation subsequently.To further verify our conclusions,we build a millimeter wave(mmWave)measurement system with a 35 GHz fabricated RIS.The measurement result corresponds well with the simulation,which shows a difference of about 3 dB in the received signal power of quad-beam compared with dual-beam,as well as dual-beam compared with single-beam,except for the impact of radiation patterns of the antennas and RIS elements.
基金supported by the Guangzhou City School Joint Found Project(SL2022A03J01009)the National Nature Science Foundation of China(Grant No.51975135)the Natural Science Foundation of Guangdong Province(2018A030310063).
文摘Solving the path planning problem of Autonomous Underwater Vehicles(AUVs)is crucial for reducing energy waste and improving operational efficiency.However,two main challenges hinder further development:Firstly,existing algorithms often treat this as a single-objective optimization problem,whereas in reality,it should be multi-objective,considering factors such as distance,safety,and smoothness simultaneously.Secondly,the limited availability of optimization results arises due to they are single-path,which fail to meet real-world conditions.To address these challenges,first of all,an improved AUV path planning model is proposed,in which the collisions of path and obstacles are classified more specifically.Subsequently,a novel Altruistic Nurturing Algorithm(ANA)inspired by natural altruism is introduced.In the algorithm,nurturing cost considering Pareto rank and crowd distance is introduced as guidance of evolution to avoid futile calculation,abandonment threshold is self-adaptive with descendant situation to help individuals escape from local optima and double selection strategy combining crowd and k-nearest neighbors selection helps to get a better-distributed Pareto front.Experimental results comparing ANA with existing algorithms in AUV path planning demonstrate its superiority.Finally,a user-friendly interface,the Multi-Objective AUV Path Planner,is designed to provide users with a group of paths for informed decisionmaking.
基金Supported by the Tianjin University of Technology Graduate R esearch Innovation Project(YJ2281).
文摘An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorithms.This algorithm considers factors such as initial position and orientation of the ship,safety range,and ship draft to determine the optimal obstacle-avoiding route from the current to the destination point for ship planning.A coordinate transformation algorithm is also applied to convert commonly used latitude and longitude coordinates of ship travel paths to easily utilized and analyzed Cartesian coordinates.The algorithm incorporates a hierarchical chart processing algorithm to handle multilayered chart data.Furthermore,the algorithm considers the impact of ship length on grid size and density when implementing chart gridification,adjusting the grid size and density accordingly based on ship length.Simulation results show that compared to traditional path planning algorithms,the sparse A^(*)algorithm reduces the average number of path points by 25%,decreases the average maximum storage node number by 17%,and raises the average path turning angle by approximately 10°,effectively improving the safety of ship planning paths.
基金Supported by the EDD of China(No.80912020104)the Science and Technology Commission of Shanghai Municipality(No.22ZR1427700 and No.23692106900).
文摘The traditional A^(*)algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,which is not conducive to the control of USV and also affects navigation safety.In this paper,these problems were addressed through the following improvements.First,the path search angle and security were comprehensively considered,and a security expansion strategy of nodes based on the 5×5 neighborhood was proposed.The A^(*)algorithm search neighborhood was expanded from 3×3 to 5×5,and safe nodes were screened out for extension via the node security expansion strategy.This algorithm can also optimize path search angles while improving path security.Second,the distance from the current node to the target node was introduced into the heuristic function.The efficiency of the A^(*)algorithm was improved,and the path was smoothed using the Floyd algorithm.For the dynamic adjustment of the weight to improve the efficiency of DWA,the distance from the USV to the target point was introduced into the evaluation function of the dynamic-window approach(DWA)algorithm.Finally,combined with the local target point selection strategy,the optimized DWA algorithm was performed for local path planning.The experimental results show the smooth and safe path planned by the fusion algorithm,which can successfully avoid dynamic obstacles and is effective and feasible in path planning for USVs.
基金Supported by National Natural Science Foundation of China(Grant No.12201471)the Special Foundation in Key Fields for Universities of Guangdong Province(Grant No.2022ZDZX1034).
文摘The Wiener index of a graph is defined to be the sum of the distances of all pairs of vertices in the graph.The kth power G^(k) of a graph G is the graph on V(G)and two vertices are adjacent if and only if their distance in G is less or equal to k.In this paper,we computed the Wiener index of the kth power of paths and cycles for any k≥2.
基金Supported by the National Natural Science Foundation of China (Grant No. 52071097)Hainan Provincial Natural Science Foundation of China (Grant No. 522MS162)Research Fund from Science and Technology on Underwater Vehicle Technology Laboratory (Grant No. 2021JCJQ-SYSJJ-LB06910)。
文摘Path planning for recovery is studied on the engineering background of double unmanned surface vehicles(USVs)towing oil booms for oil spill recovery.Given the influence of obstacles on the sea,the improved artificial potential field(APF)method is used for path planning.For addressing the two problems of unreachable target and local minimum in the APF,three improved algorithms are proposed by combining the motion performance constraints of the double USV system.These algorithms are then combined as the final APF-123 algorithm for oil spill recovery.Multiple sets of simulation tests are designed according to the flaws of the APF and the process of oil spill recovery.Results show that the proposed algorithms can ensure the system’s safety in tracking oil spills in a complex environment,and the speed is increased by more than 40%compared with the APF method.
基金National Natural Science Foundation of China(Grant No.52472417)to provide fund for conducting experiments.
文摘Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.
文摘Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.
文摘Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.
基金supported by NSF China(No.61960206002,62020106005,42050105,62061146002)Shanghai Pilot Program for Basic Research-Shanghai Jiao Tong University。
文摘This paper focuses on optimally determining the existence of connected paths between some given nodes in random ring-based graphs.Serving as a fundamental underlying structure in network modeling,ring topology appears as commonplace in many realistic scenarios.Regarding this,we consider graphs composed of rings,with some possible connected paths between them.Without prior knowledge of the exact node permutations on rings,the existence of each edge can be unraveled through edge testing at a unit cost in one step.The problem examined is that of determining whether the given nodes are connected by a path or separated by a cut,with the minimum expected costs involved.Dividing the problem into different cases based on different topologies of the ring-based networks,we propose the corresponding policies that aim to quickly seek the paths between nodes.A common feature shared by all those policies is that we stick to going in the same direction during edge searching,with edge testing in each step only involving the test between the source and the node that has been tested most.The simple searching rule,interestingly,can be interpreted as a delightful property stemming from the neat structure of ring-based networks,which makes the searching process not rely on any sophisticated behaviors.We prove the optimality of the proposed policies by calculating the expected cost incurred and making a comparison with the other class of strategies.The effectiveness of the proposed policies is also verified through extensive simulations,from which we even disclose three extra intriguing findings:i)in a onering network,the cost will grow drastically with the number of designated nodes when the number is small and will grow slightly when that number is large;ii)in ring-based network,Depth First is optimal in detecting the connectivity between designated nodes;iii)the problem of multi-ring networks shares large similarity with that of two-ring networks,and a larger number of ties between rings will not influence the expected cost.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62173312 and 61803348in part by the National Major Scientific Instruments Development Project under Grant No.61927807+3 种基金in part by the Program for the Innovative Talents of Higher Education Institutions of ShanxiShanxi Province Science Foundation for Excellent Youthsin part by the Shanxi"1331 Project"Key Subjects Construction(1331KSC)in part by Graduate Innovation Project of Shanxi Province under Grant No.2021Y617。
文摘This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.
基金the National Natural Science Foundation of China (Nos.52304123 and 52104077)the Postdoctoral Fellowship Program of CPSF (No.GZB20230914)+1 种基金the China Postdoctoral Science Foundation (No.2023M730412)the National Key Research and Development Program for Young Scientists (No.2021YFC2900400)。
文摘Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.
基金supported in part by National Natural Science Foundation of China under Grants 62122069, 62071431, 62072490 and 62301490in part by Science and Technology Development Fund of Macao SAR, China under Grant 0158/2022/A+2 种基金in part by the Guangdong Basic and Applied Basic Research Foundation (2022A1515011287)in part by MYRG202000107-IOTSCin part by FDCT SKL-IOTSC (UM)-2021-2023
文摘With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.
基金financially supported by the National Natural Science Foundation of China(Nos.52304265,52174216,and 52274145)the Natural Science Foundation of Jiangsu Province(No.BK20221121)the State Key Laboratory of Mining Disaster Prevention and Control(Shandong University of Science and Technology)and Ministry of Education(No.JMDPC202301)。
文摘Both bulk stress(σ_(i i))and stress path(SP)significantly affect the transportation characteristics of deep gas during reservoir pressure depletion.Therefore,the experimental study of horizontal stress unloading on seepage behavior of gas-bearing coal under constantσi i-constraints is performed.The results show that coal permeability is affected by horizontal stress anisotropy(σ_(H)≠σh),and the contribution of minor horizontal stress to permeability is related to the differential response of horizontal strain.The slippage phenomenon is prominent in deep high-stress regime,especially in low reservoir pressure.σ_(i i)and SP jointly determine the manifestation of slippage effect and the strength of stress sensitivity(γ)of permeability.Deep reservoir implies an incremental percentage of slip-based permeability,and SP weakens the slippage effect by changing the elastic–plastic state of coal.However,γis negatively correlated with slippage effect.From the Walsh model,narrow(low aspect-ratio)fractures within the coal under unloading SP became the main channel for gas seepage,and bring the effective stress coefficient of permeability(χ)less than 1 for both low-stress elastic and high-stress damaged coal.With the raise of the effective stress,the effect of pore-lined clay particles on permeability was enhanced,inducing an increase inχfor highstress elastic coal.
基金supported by Shanghai Artificial Intelligence Laboratory.
文摘This paper addresses the estimation problem of an unknown drift parameter matrix for a fractional Ornstein-Uhlenbeck process in a multi-dimensional setting.To tackle this problem,we propose a novel approach based on rough path theory that allows us to construct pathwise rough path estimators from both continuous and discrete observations of a single path.Our approach is particularly suitable for high-frequency data.To formulate the parameter estimators,we introduce a theory of pathwise Itôintegrals with respect to fractional Brownian motion.By establishing the regularity of fractional Ornstein-Uhlenbeck processes and analyzing the long-term behavior of the associated Lévy area processes,we demonstrate that our estimators are strongly consistent and pathwise stable.Our findings offer a new perspective on estimating the drift parameter matrix for fractional Ornstein-Uhlenbeck processes in multi-dimensional settings,and may have practical implications for fields including finance,economics,and engineering.
基金the National Natural Science Foundation of China(Grant No.42274119)the Liaoning Revitalization Talents Program(Grant No.XLYC2002082)+1 种基金National Key Research and Development Plan Key Special Projects of Science and Technology Military Civil Integration(Grant No.2022YFF1400500)the Key Project of Science and Technology Commission of the Central Military Commission.
文摘This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.
文摘CO_(2) conversion into value-added products by electro-, photoand plasma catalysis under mild operating conditions(ambient temperature and pressure) is an emerging area to achieve carbon circularity by producing chemicals and fuels using directly renewable energy. Among all CO_(2) conversion approaches, the electrocatalytic reduction of CO_(2) is the most mature technology, capable of achieving high productivity(i.e. high current densities) at large scale, especially for producing carbon monoxide(CO), but with many examples showing selectivity to C_(2) carbon products.
文摘The path-following control design for an autonomous underwater vehicle(AUV)requires prior full or partial knowledge about the mathematical model defined through Newton’s second law based on a geometrical investigation.AUV dynamics are highly nonlinear and time-varying,facing unpredictable disturbances due to AUVs operating in deep,hazardous oceanic environments.Consequently,navigation guidance and control systems for AUVs must learn and adapt to the time-varying dynamics of the nonlinear fully coupled vehicle model in the presence of highly unstructured underwater operating conditions.Many control engineers focus on the application of robust model-free adaptive control techniques in AUV maneuvers.Hence,the main goal is to design a novel salp swarm optimization of super twisting algorithm-based secondorder sliding mode controller for the planar path-following control of an AUV through regulation of the heading angle parameter.The finite time for tracking error convergence in the horizontal plane is provided through the control structure architecture,particularly for lateral deviations from the desired path.The proposed control law is designed such that it steers a robotic vehicle to track a predefined planar path at a constant speed determined by an end-user,without any temporal specification.Finally,the efficacy and tracking accuracy are evaluated through comparative analysis based on simulation and experimental hardware-in-loop assessment without violating the input constraints.Moreover,the proposed control law can handle parametric uncertainties and unpredictable disturbances such as ocean currents,wind,and measurement noise.
