This paper provides a new obstacle avoidance control method for cars based on big data and just-in-time modeling. Just-in-time modeling is a new kind of data-driven control technique in the age of big data and is used...This paper provides a new obstacle avoidance control method for cars based on big data and just-in-time modeling. Just-in-time modeling is a new kind of data-driven control technique in the age of big data and is used in various real systems. The main property of the proposed method is that a gain and a control time which are parameters in the control input to avoid an encountered obstacle are computed from a database which includes a lot of driving data in various situations. Especially, the important advantage of the method is small computation time, and hence it realizes real-time obstacle avoidance control for cars. From some numerical simulations, it is showed that the new control method can make the car avoid various obstacles efficiently in comparison with the previous method.展开更多
One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key ro...One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key role in QOS routing. We propose a random mobility model based on discretetime Markov chain, called ODM. ODM provides a mathematical framework for calculating some parameters to show the future status of mobility nodes, for instance, the state transition probability matrix of nodes, the probability that an edge is valid, the average number of valid-edges and the probability of a request packet found a valid route. Furthermore, ODM can account for obstacle environment. The state transition probability matrix of nodes can quantify the impact of obstacles. Several theorems are given and proved by using the ODM. Simulation results show that the calculated value can forecast the future status of mobility nodes.展开更多
Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the ...Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model＇s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.展开更多
Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccu...Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccurate driver operations,and mismatched model errors.Furthermore,misleading sensing information or malicious attacks in vehicular wireless networks can jeopardize CAVs’perception and platoon safety.In this paper,we develop a two-dimensional robust control method for a mixed platoon,including a single leading CAV and multiple following HDVs that incorpo-rate robust information sensing and platoon control.To effectively detect and locate unknown obstacles ahead of the leading CAV,we propose a cooperative vehicle-infrastructure sensing scheme and integrate it with an adaptive model predictive control scheme for the leading CAV.This sensing scheme fuses information from multiple nodes while suppressing malicious data from attackers to enhance robustness and attack resilience in a distributed and adaptive manner.Additionally,we propose a distributed car-following control scheme with robustness to guarantee the following HDVs,considering uncertain disturbances.We also provide theoretical proof of the string stability under this control framework.Finally,extensive simulations are conducted to validate our approach.The simulation results demonstrate that our method can effectively filter out misleading sensing information from malicious attackers,significantly reduce the mean-square deviation in obstacle sensing,and approach the theoretical error lower bound.Moreover,the proposed control method successfully achieves obstacle avoidance for the mixed platoon while ensuring stability and robustness in the face of external attacks and uncertain disturbances.展开更多
A robot intelligent path planning system RIPPS is developed, which can be utilized for a robot off line programming tool. The system consists of three parts: geometric modeler, kinematic modeler and path planer. The...A robot intelligent path planning system RIPPS is developed, which can be utilized for a robot off line programming tool. The system consists of three parts: geometric modeler, kinematic modeler and path planer. The geometric modeler is used to construct the robot working environment cluttered with obstacles and the robot kinematic modeler to define robot manipulators by the input parameters. Giving robot start and the goal configurations, the path planer can produce a quasi optimal path. By transforming obstacles into the C space to form C obstacles, the path searching is performed in C space. The planning simulations are performed on a SGI workstation, the future research is to implement the planer on a commercial robot manipulators.展开更多
In order toclarify regional ecological security status and formation mechanism of regional ecological security barriers in underdeveloped regions of China,we took Yunnan province as a case to evaluate its regional eco...In order toclarify regional ecological security status and formation mechanism of regional ecological security barriers in underdeveloped regions of China,we took Yunnan province as a case to evaluate its regional ecological security by using entropy matter-element model,comprehensive index and GIS spatial method,and we diagnosed itsobstacle factors through obstacle degree model. We found a low overall level of regional ecological security in Yunnan. Only Kunmingfell into the good level, 68% of the regions were below the critical safe level. For the vast majority of regions in Yunnan, their regional ecological security was unstable. The indexes related to per capita resources, geological and topographyenvironment, economic, and technologywere at the unsafe or dangerous level.The indexes related to urban expansion, level of income, cultivated land quality were at the level of critical safety. The indexes concerning urban management capacity, airqualityand waterenvironment were at the good or ideallevel. Yunnan's regional ecological security was not good due to natural obstructive environment itself, simultaneously lower backward economic and social level restricted the ability of ecological security response to manage ragile ecological environment. The results of the composite index wereroughly consistent with those of the entropy weight matterelement model. The mean values of the classification index,from high to low, were: the state index>the response index>the pressure index. The state index and the response index had a significant mutual promotion to each other.The regions with good composite index, state index and response index mainly distributed in the central regions of Yunnan Province. Spatial autocorrelation of regional ecological security level in Yunnan was not obvious. Water resources, economic and social development were main obstacle factors of the regional ecological security.When distinguishing with obstacle type, Kunming belonged to natural ecological environment barrier type, while other regions belonged to economic and social barrier type.展开更多
Based on statistical data and population flow data for 2016,and using entropy weight TOPSIS and the obstacle degree model,the centrality of cities in the Yangtze River Economic Belt(YREB)together with the factors infl...Based on statistical data and population flow data for 2016,and using entropy weight TOPSIS and the obstacle degree model,the centrality of cities in the Yangtze River Economic Belt(YREB)together with the factors influencing centrality were measured.In addition,data for the population flow were used to analyze the relationships between cities and to verify centrality.The results showed that:(1)The pattern of centrality conforms closely to the pole-axis theory and the central geography theory.Two axes,corresponding to the Yangtze River and the Shanghai-Kunming railway line,interconnect cities of different classes.On the whole,the downstream cities have higher centrality,well-defined gradients and better development of city infrastructure compared with cities in the middle and upper reaches.(2)The economic scale and size of the population play a fundamental role in the centrality of cities,and other factors reflect differences due to different city classes.For most of the coastal cities or the capital cities in the central and western regions,factors that require long-term development such as industrial facilities,consumption,research and education provide the main competitive advantages.For cities that are lagging behind in development,transportation facilities,construction of infrastructure and fixed asset investment have become the main methods to achieve development and enhance competitiveness.(3)The mobility of city populations has a significant correlation with the centrality score,the correlation coefficients for the relationships between population mobility and centrality are all greater than 0.86(P<0.01).The population flow is mainly between high-class cities,or high-class and low-class cities,reflecting the high centrality and huge radiating effects of high-class cities.Furthermore,the cities in the YREB are closely linked to Guangdong and Beijing,reflecting the dominant economic status of Guangdong with its geographical proximity to the YREB and Beijing's enormous influence as the national political and cultural center,respectively.展开更多
The paper proposes a Virtual Target Guidance(VTG)-based distributed Model Predictive Control(MPC) scheme for formation control of multiple Unmanned Aerial Vehicles(UAVs).First, a framework of distributed MPC scheme is...The paper proposes a Virtual Target Guidance(VTG)-based distributed Model Predictive Control(MPC) scheme for formation control of multiple Unmanned Aerial Vehicles(UAVs).First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem(FHOCP) can be solved by swarm intelligent optimization algorithm.Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance.Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function.Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.展开更多
In this article we specify an individual-based foraging swarm （i.e., group of agents） model with individuals that move in an n-dimensional multi-obstacle environment. The motion of each individual （i） is determine...In this article we specify an individual-based foraging swarm （i.e., group of agents） model with individuals that move in an n-dimensional multi-obstacle environment. The motion of each individual （i） is determined by three factors： i） attraction to the local object position （x^-io＋） which is decided by the local information about the individuals＇ position that individual i can find; ii） repulsion from the other individuals on short distances; and iii） attraction to the global object position （xgoal） or repulsion from the obstacles in the environment, The emergent behavior of the swarm motion is the result of a balance between inter-individual interaction and the simultaneous interactions of the swarm members with their environment. We study the stability properties of the collective behavior of the swarm based on Lyapunov stability theory. The simulations show that the swarm can converge to goal regions and diverge from obstacle regions of the environment while maintaining cohesive.展开更多
In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was stu...In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4. 6 cm, which meets the application requirements of the robot.展开更多
目的基于健康服务领域研究成果应用的整合性行动促进框架(integrated-promoting action on research implement action in health services framework,i-PARIHS)模式构建创伤骨科患者手术部位感染(surgical site infection,SSI)防控的...目的基于健康服务领域研究成果应用的整合性行动促进框架(integrated-promoting action on research implement action in health services framework,i-PARIHS)模式构建创伤骨科患者手术部位感染(surgical site infection,SSI)防控的审查指标,分析临床实践障碍因素并提出改进策略。方法成立循证团队、文献检索、总结最佳证据、制定审查指标,于2024年7—8月开展基线调查,调查创伤骨科医护、麻醉手术中心医护执行率及患者知晓率,从“变革、接受者、组织环境”3个要素识别障碍因素,拟定变革策略。结果根据最佳证据评估并裁剪审查指标共23项,涵盖评估与监测、内外环境优化、术中关注重点、跟踪与随访和环境因素控制5个方面,涉及创伤骨科医生的14个指标平均执行率为72.14%,涉及病房护士的14个指标平均执行率为74.11%,涉及麻醉医生的5个指标平均执行率为60.50%,涉及手术室护士的10个指标平均执行率为61.75%,涉及患者知晓的5个直接指标平均知晓率为44.54%;障碍因素分析后拟定相应促进因素8条,拟定变革策略17条。结论临床实践与循证证据存在差距,基于i-PARIHS模式构建的审查指标与障碍分析为SSI防控提供了系统化改进框架,但需进一步验证策略的临床效果。展开更多
A method of environment mapping using laser-based light detection and ranging （LIDAR） is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also fa...A method of environment mapping using laser-based light detection and ranging （LIDAR） is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks （CBFD） is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm （ISODATA）.展开更多
As a GIS tool,visibility analysis is used in many areas to evaluate both visible and non-visible places.Visibility analysis builds on a digital surface model describing the terrain morphology,including the position an...As a GIS tool,visibility analysis is used in many areas to evaluate both visible and non-visible places.Visibility analysis builds on a digital surface model describing the terrain morphology,including the position and shapes of all objects that can sometimes act as visibility barriers.However,some barriers,for example vegetation,may be permeable to a certain degree.Despite extensive research and use of visibility analysis in different areas,standard GIS tools do not take permeability into account.This article presents a new method to calculate visibility through partly permeable obstacles.The method is based on a quasi-Monte Carlo simulation with 100 iterations of visibility calculation.Each iteration result represents 1%of vegetation permeability,which can thus range from 1%to 100%visibility behind vegetation obstacles.The main advantage of the method is greater accuracy of visibility results and easy implementation on any GIS software.The incorporation of the proposed method in GIS software would facilitate work in many fields,such as architecture,archaeology,radio communication,and the military.展开更多
Considering that the inevitable disturbances and coupled constraints pose an ongoing challenge to distributed control algorithms,this paper proposes a distributed robust model predictive control(MPC)algorithm for a mu...Considering that the inevitable disturbances and coupled constraints pose an ongoing challenge to distributed control algorithms,this paper proposes a distributed robust model predictive control(MPC)algorithm for a multi-agent system with additive external disturbances and obstacle and collision avoidance constraints.In particular,all the agents are allowed to solve optimization problems simultaneously at each time step to obtain their control inputs,and the obstacle and collision avoidance are accomplished in the context of full-dimensional controlled objects and obstacles.To achieve the collision avoidance between agents in the distributed framework,an assumed state trajectory is introduced for each agent which is transmitted to its neighbors to construct the polyhedral over-approximations of it.Then the polyhedral over-approximations of the agent and the obstacles are used to smoothly reformulate the original nonconvex obstacle and collision avoidance constraints.And a compatibility constraint is designed to restrict the deviation between the predicted and assumed trajectories.Moreover,recursive feasibility of each local MPC optimization problem with all these constraints derived and input-to-state stability of the closed-loop system can be ensured through a sufficient condition on controller parameters.Finally,simulations with four agents and two obstacles demonstrate the efficiency of the proposed algorithm.展开更多
Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especi...Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especially in a relatively narrow man–machine dynamic environments such as warehouses and laboratories.In this study,human and robot behaviors in man–machine environments are analyzed,and a man–machine social force model is established to study the robot obstacle avoidance speed.Four typical man–machine behavior patterns are investigated to design the robot behavior strategy.Based on the social force model and man–machine behavior patterns,the fuzzy-PID trajectory tracking control method and the autonomous obstacle avoidance behavior strategy of the mobile robot in inspecting hazardous gases in a relatively narrow man–machine dynamic environment are proposed to determine the optimal robot speed for obstacle avoidance.The simulation analysis results show that compared with the traditional PID control method,the proposed controller has a position error of less than 0.098 m,an angle error of less than 0.088 rad,a smaller steady-state error,and a shorter convergence time.The crossing and encountering pattern experiment results show that the proposed behavior strategy ensures that the robot maintains a safe distance from humans while performing trajectory tracking.This research proposes a combination autonomous behavior strategy for mobile robots inspecting hazardous gases,ensuring that the robot maintains the optimal speed to achieve dynamic obstacle avoidance,reducing human anxiety and increasing comfort in a relatively narrow man–machine environment.展开更多
文摘This paper provides a new obstacle avoidance control method for cars based on big data and just-in-time modeling. Just-in-time modeling is a new kind of data-driven control technique in the age of big data and is used in various real systems. The main property of the proposed method is that a gain and a control time which are parameters in the control input to avoid an encountered obstacle are computed from a database which includes a lot of driving data in various situations. Especially, the important advantage of the method is small computation time, and hence it realizes real-time obstacle avoidance control for cars. From some numerical simulations, it is showed that the new control method can make the car avoid various obstacles efficiently in comparison with the previous method.
基金Acknowledgements This work is supported by the Postdoctoral Science Foundation of China under Grant No.20080431142.
文摘One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key role in QOS routing. We propose a random mobility model based on discretetime Markov chain, called ODM. ODM provides a mathematical framework for calculating some parameters to show the future status of mobility nodes, for instance, the state transition probability matrix of nodes, the probability that an edge is valid, the average number of valid-edges and the probability of a request packet found a valid route. Furthermore, ODM can account for obstacle environment. The state transition probability matrix of nodes can quantify the impact of obstacles. Several theorems are given and proved by using the ODM. Simulation results show that the calculated value can forecast the future status of mobility nodes.
基金Foundation item： Supported by the National Natural Science Foundation of China under Grant No.61100005.
文摘Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model＇s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.
基金supported by the National Key Research and the Development Program of China(2022YFC3803700)the National Natural Science Foundation of China(52202391 and U20A20155).
文摘Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccurate driver operations,and mismatched model errors.Furthermore,misleading sensing information or malicious attacks in vehicular wireless networks can jeopardize CAVs’perception and platoon safety.In this paper,we develop a two-dimensional robust control method for a mixed platoon,including a single leading CAV and multiple following HDVs that incorpo-rate robust information sensing and platoon control.To effectively detect and locate unknown obstacles ahead of the leading CAV,we propose a cooperative vehicle-infrastructure sensing scheme and integrate it with an adaptive model predictive control scheme for the leading CAV.This sensing scheme fuses information from multiple nodes while suppressing malicious data from attackers to enhance robustness and attack resilience in a distributed and adaptive manner.Additionally,we propose a distributed car-following control scheme with robustness to guarantee the following HDVs,considering uncertain disturbances.We also provide theoretical proof of the string stability under this control framework.Finally,extensive simulations are conducted to validate our approach.The simulation results demonstrate that our method can effectively filter out misleading sensing information from malicious attackers,significantly reduce the mean-square deviation in obstacle sensing,and approach the theoretical error lower bound.Moreover,the proposed control method successfully achieves obstacle avoidance for the mixed platoon while ensuring stability and robustness in the face of external attacks and uncertain disturbances.
文摘A robot intelligent path planning system RIPPS is developed, which can be utilized for a robot off line programming tool. The system consists of three parts: geometric modeler, kinematic modeler and path planer. The geometric modeler is used to construct the robot working environment cluttered with obstacles and the robot kinematic modeler to define robot manipulators by the input parameters. Giving robot start and the goal configurations, the path planer can produce a quasi optimal path. By transforming obstacles into the C space to form C obstacles, the path searching is performed in C space. The planning simulations are performed on a SGI workstation, the future research is to implement the planer on a commercial robot manipulators.
基金funded by the National Science-technology Support Plan Projects of China (Grant No.2015BAD07B0105)Yunnan Education Department Fundof China (2014Y315)
文摘In order toclarify regional ecological security status and formation mechanism of regional ecological security barriers in underdeveloped regions of China,we took Yunnan province as a case to evaluate its regional ecological security by using entropy matter-element model,comprehensive index and GIS spatial method,and we diagnosed itsobstacle factors through obstacle degree model. We found a low overall level of regional ecological security in Yunnan. Only Kunmingfell into the good level, 68% of the regions were below the critical safe level. For the vast majority of regions in Yunnan, their regional ecological security was unstable. The indexes related to per capita resources, geological and topographyenvironment, economic, and technologywere at the unsafe or dangerous level.The indexes related to urban expansion, level of income, cultivated land quality were at the level of critical safety. The indexes concerning urban management capacity, airqualityand waterenvironment were at the good or ideallevel. Yunnan's regional ecological security was not good due to natural obstructive environment itself, simultaneously lower backward economic and social level restricted the ability of ecological security response to manage ragile ecological environment. The results of the composite index wereroughly consistent with those of the entropy weight matterelement model. The mean values of the classification index,from high to low, were: the state index>the response index>the pressure index. The state index and the response index had a significant mutual promotion to each other.The regions with good composite index, state index and response index mainly distributed in the central regions of Yunnan Province. Spatial autocorrelation of regional ecological security level in Yunnan was not obvious. Water resources, economic and social development were main obstacle factors of the regional ecological security.When distinguishing with obstacle type, Kunming belonged to natural ecological environment barrier type, while other regions belonged to economic and social barrier type.
基金National Natural Science Foundation of China,No.41871176The“Hua Bo”Plan of Central China Normal UniversityPostgraduate Education Innovation Subsidy Project of Central China Normal University,No.2018CXZZ004。
文摘Based on statistical data and population flow data for 2016,and using entropy weight TOPSIS and the obstacle degree model,the centrality of cities in the Yangtze River Economic Belt(YREB)together with the factors influencing centrality were measured.In addition,data for the population flow were used to analyze the relationships between cities and to verify centrality.The results showed that:(1)The pattern of centrality conforms closely to the pole-axis theory and the central geography theory.Two axes,corresponding to the Yangtze River and the Shanghai-Kunming railway line,interconnect cities of different classes.On the whole,the downstream cities have higher centrality,well-defined gradients and better development of city infrastructure compared with cities in the middle and upper reaches.(2)The economic scale and size of the population play a fundamental role in the centrality of cities,and other factors reflect differences due to different city classes.For most of the coastal cities or the capital cities in the central and western regions,factors that require long-term development such as industrial facilities,consumption,research and education provide the main competitive advantages.For cities that are lagging behind in development,transportation facilities,construction of infrastructure and fixed asset investment have become the main methods to achieve development and enhance competitiveness.(3)The mobility of city populations has a significant correlation with the centrality score,the correlation coefficients for the relationships between population mobility and centrality are all greater than 0.86(P<0.01).The population flow is mainly between high-class cities,or high-class and low-class cities,reflecting the high centrality and huge radiating effects of high-class cities.Furthermore,the cities in the YREB are closely linked to Guangdong and Beijing,reflecting the dominant economic status of Guangdong with its geographical proximity to the YREB and Beijing's enormous influence as the national political and cultural center,respectively.
基金supported in part by the National Natural Science Foundation of China(No.61803009)Fundamental Research Funds for the Central Universities,China(No.YWF-19-BJ-J-205)Aeronautical Science Foundation of China(No.20175851032)。
文摘The paper proposes a Virtual Target Guidance(VTG)-based distributed Model Predictive Control(MPC) scheme for formation control of multiple Unmanned Aerial Vehicles(UAVs).First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem(FHOCP) can be solved by swarm intelligent optimization algorithm.Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance.Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function.Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.
基金This work was supported by the National Natural Science Foundation of China (No. 60574088).
文摘In this article we specify an individual-based foraging swarm （i.e., group of agents） model with individuals that move in an n-dimensional multi-obstacle environment. The motion of each individual （i） is determined by three factors： i） attraction to the local object position （x^-io＋） which is decided by the local information about the individuals＇ position that individual i can find; ii） repulsion from the other individuals on short distances; and iii） attraction to the global object position （xgoal） or repulsion from the obstacles in the environment, The emergent behavior of the swarm motion is the result of a balance between inter-individual interaction and the simultaneous interactions of the swarm members with their environment. We study the stability properties of the collective behavior of the swarm based on Lyapunov stability theory. The simulations show that the swarm can converge to goal regions and diverge from obstacle regions of the environment while maintaining cohesive.
基金Supported by the Ministerial Level Advanced Research Foundation(40401060305)
文摘In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4. 6 cm, which meets the application requirements of the robot.
文摘目的基于健康服务领域研究成果应用的整合性行动促进框架(integrated-promoting action on research implement action in health services framework,i-PARIHS)模式构建创伤骨科患者手术部位感染(surgical site infection,SSI)防控的审查指标,分析临床实践障碍因素并提出改进策略。方法成立循证团队、文献检索、总结最佳证据、制定审查指标,于2024年7—8月开展基线调查,调查创伤骨科医护、麻醉手术中心医护执行率及患者知晓率,从“变革、接受者、组织环境”3个要素识别障碍因素,拟定变革策略。结果根据最佳证据评估并裁剪审查指标共23项,涵盖评估与监测、内外环境优化、术中关注重点、跟踪与随访和环境因素控制5个方面,涉及创伤骨科医生的14个指标平均执行率为72.14%,涉及病房护士的14个指标平均执行率为74.11%,涉及麻醉医生的5个指标平均执行率为60.50%,涉及手术室护士的10个指标平均执行率为61.75%,涉及患者知晓的5个直接指标平均知晓率为44.54%;障碍因素分析后拟定相应促进因素8条,拟定变革策略17条。结论临床实践与循证证据存在差距,基于i-PARIHS模式构建的审查指标与障碍分析为SSI防控提供了系统化改进框架,但需进一步验证策略的临床效果。
基金Supported by the National Natural Science Foundation of China(61103157)
文摘A method of environment mapping using laser-based light detection and ranging （LIDAR） is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks （CBFD） is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm （ISODATA）.
基金This work was financially supported by project 133/2016/RPP-TO-1/b“Teaching of advanced techniques for geodata processing for follow-up study of geoinformatics”.
文摘As a GIS tool,visibility analysis is used in many areas to evaluate both visible and non-visible places.Visibility analysis builds on a digital surface model describing the terrain morphology,including the position and shapes of all objects that can sometimes act as visibility barriers.However,some barriers,for example vegetation,may be permeable to a certain degree.Despite extensive research and use of visibility analysis in different areas,standard GIS tools do not take permeability into account.This article presents a new method to calculate visibility through partly permeable obstacles.The method is based on a quasi-Monte Carlo simulation with 100 iterations of visibility calculation.Each iteration result represents 1%of vegetation permeability,which can thus range from 1%to 100%visibility behind vegetation obstacles.The main advantage of the method is greater accuracy of visibility results and easy implementation on any GIS software.The incorporation of the proposed method in GIS software would facilitate work in many fields,such as architecture,archaeology,radio communication,and the military.
基金the National Natural Science Foundation of China(Nos.62173036,62003040,62122014)the Beijing Institute of Technology Research Fund Program for Young Scholars.
文摘Considering that the inevitable disturbances and coupled constraints pose an ongoing challenge to distributed control algorithms,this paper proposes a distributed robust model predictive control(MPC)algorithm for a multi-agent system with additive external disturbances and obstacle and collision avoidance constraints.In particular,all the agents are allowed to solve optimization problems simultaneously at each time step to obtain their control inputs,and the obstacle and collision avoidance are accomplished in the context of full-dimensional controlled objects and obstacles.To achieve the collision avoidance between agents in the distributed framework,an assumed state trajectory is introduced for each agent which is transmitted to its neighbors to construct the polyhedral over-approximations of it.Then the polyhedral over-approximations of the agent and the obstacles are used to smoothly reformulate the original nonconvex obstacle and collision avoidance constraints.And a compatibility constraint is designed to restrict the deviation between the predicted and assumed trajectories.Moreover,recursive feasibility of each local MPC optimization problem with all these constraints derived and input-to-state stability of the closed-loop system can be ensured through a sufficient condition on controller parameters.Finally,simulations with four agents and two obstacles demonstrate the efficiency of the proposed algorithm.
基金Research and Development Program of Xi’an Modern Chemistry Research Institute of Chnia(Grant No.204J201916234/6)Key Project of Liuzhou Science and Technology Bureau of China(Grant No.2020PAAA0601).
文摘Selecting the optimal speed for dynamic obstacle avoidance in complex man–machine environments is a challenging problem for mobile robots inspecting hazardous gases.Consideration of personal space is important,especially in a relatively narrow man–machine dynamic environments such as warehouses and laboratories.In this study,human and robot behaviors in man–machine environments are analyzed,and a man–machine social force model is established to study the robot obstacle avoidance speed.Four typical man–machine behavior patterns are investigated to design the robot behavior strategy.Based on the social force model and man–machine behavior patterns,the fuzzy-PID trajectory tracking control method and the autonomous obstacle avoidance behavior strategy of the mobile robot in inspecting hazardous gases in a relatively narrow man–machine dynamic environment are proposed to determine the optimal robot speed for obstacle avoidance.The simulation analysis results show that compared with the traditional PID control method,the proposed controller has a position error of less than 0.098 m,an angle error of less than 0.088 rad,a smaller steady-state error,and a shorter convergence time.The crossing and encountering pattern experiment results show that the proposed behavior strategy ensures that the robot maintains a safe distance from humans while performing trajectory tracking.This research proposes a combination autonomous behavior strategy for mobile robots inspecting hazardous gases,ensuring that the robot maintains the optimal speed to achieve dynamic obstacle avoidance,reducing human anxiety and increasing comfort in a relatively narrow man–machine environment.
