Space emergency launching is to send a satellite into space by using a rapid responsive solid rocket in the bounded time to implement the emergency Earth observation mission.The key and difficult points mainly include...Space emergency launching is to send a satellite into space by using a rapid responsive solid rocket in the bounded time to implement the emergency Earth observation mission.The key and difficult points mainly include the business process construction of launching mission planning,validation of the effectiveness of the launching scheme,etc.This paper pro-poses the agile space emergency launching mission planning simulation and verification method,which systematically con-structs the overall technical framework of space emergency launching mission planning with multi-field area,multi-platform and multi-task parallel under the constraint of resource schedul-ing for the first time.It supports flexible reconstruction of mis-sion planning processes such as launching target planning,tra-jectory planning,path planning,action planning and launching time analysis,and can realize on-demand assembly of operation links under different mission scenarios and different plan condi-tions,so as to quickly modify and generate launching schemes.It supports the fast solution of rocket trajectory data and the accurate analysis of multi-point salvo time window recheck and can realize the fast conflict resolution of launching missions in the dimensions of launching position and launching window sequence.It supports lightweight scenario design,modular flexi-ble simulation,based on launching style,launching platform,launching rules,etc.,can realize the independent mapping of mission planning results to two-dimensional and three-dimen-sional visual simulation models,so as to achieve a smooth con-nection between mission planning and simulation.展开更多
Cooperative search-attack is an important application of unmanned aerial vehicle(UAV)swarm in military field.The coupling between path planning and task allocation,the heterogeneity of UAVs,and the dynamic nature of t...Cooperative search-attack is an important application of unmanned aerial vehicle(UAV)swarm in military field.The coupling between path planning and task allocation,the heterogeneity of UAVs,and the dynamic nature of task environment greatly increase the complexity and difficulty of the UAV swarm cooperative search-attack mission planning problem.Inspired by the collaborative hunting behavior of wolf pack,a distributed selforganizing method for UAV swarm search-attack mission planning is proposed.First,to solve the multi-target search problem in unknown environments,a wolf scouting behavior-inspired cooperative search algorithm for UAV swarm is designed.Second,a distributed self-organizing task allocation algorithm for UAV swarm cooperative attacking of targets is proposed by analyzing the flexible labor division behavior of wolves.By abstracting the UAV as a simple artificial wolf agent,the flexible motion planning and group task coordinating for UAV swarm can be realized by self-organizing.The effectiveness of the proposed method is verified by a set of simulation experiments,the stability and scalability are evaluated,and the integrated solution for the coupled path planning and task allocation problems for the UAV swarm cooperative search-attack task can be well performed.展开更多
This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-s...This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-strip area,real time download request,and stereoscopic request) and complex satellite actions,such as observe action and data download action,are considered in this paper. Through reasonable analysis of specialties and operational constraints of agile satellites in observing process,the mission scheduling model under multiple objective conditions is constructed. A genetic algorithm combined with heuristic rules is designed to solve problem. Genetic algorithm is designed to arrange user missions and heuristic rules are used to arrange satellite actions. Experiment results suggest that our algorithm works well for the agile Earth-observing satellite scheduling problem.展开更多
Satellite observation schedule is investigated in this paper.A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite.The newly developed method can make the...Satellite observation schedule is investigated in this paper.A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite.The newly developed method can make the satellite observe more targets and therefore save observation resources.First,for the densely distributed target points,a preprocessing scheme based on task clustering is proposed.The target points are clustered according to the distance condition.Second,the local observation path is generated by Tabu algorithm in the inner layer of cluster regions.Third,considering the scatter and cluster sets,the global observation path is obtained by adopting Tabu algorithm in the outer layer.Simulation results show that the algorithm can effectively reduce the task planning time of large-scale point targets while ensuring the optimal solution quality.展开更多
This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time ...This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time of the astronauts properly. A domain model is developed by using the ontology theory to describe the concepts, constraints and relations of the planning domain formally, abstractly and normatively. A method based on time iteration is adopted to solve the short-term planning problem. Meanwhile, the resolving strategies are proposed to resolve different kinds of conflicts induced by the constraints of power, heat, resource, astronaut and relationship. The proposed approach is evaluated in a test case with fifteen missions, thirteen resources and three astronauts. The results show that the developed domain ontology model is reasonable, and the time iteration method using the proposed resolving strategies can successfully obtain the plan satisfying all considered constraints.展开更多
Reconnaissance mission planning of multiple unmanned aerial vehicles(UAVs)under an adversarial environment is a discrete combinatorial optimization problem which is proved to be a non-deterministic polynomial(NP)-comp...Reconnaissance mission planning of multiple unmanned aerial vehicles(UAVs)under an adversarial environment is a discrete combinatorial optimization problem which is proved to be a non-deterministic polynomial(NP)-complete problem.The purpose of this study is to research intelligent multiUAVs reconnaissance mission planning and online re-planning algorithm under various constraints in mission areas.For numerous targets scattered in the wide area,a reconnaissance mission planning and re-planning system is established,which includes five modules,including intelligence analysis,sub-mission area division,mission sequence planning,path smoothing,and online re-planning.The intelligence analysis module depicts the attribute of targets and the heterogeneous characteristic of UAVs and computes the number of sub-mission areas on consideration of voyage distance constraints.In the sub-mission area division module,an improved K-means clustering algorithm is designed to divide the reconnaissance mission area into several sub-mission areas,and each sub-mission is detected by the UAV loaded with various detective sensors.To control reconnaissance cost,the sampling and iteration algorithms are proposed in the mission sequence planning module,which are utilized to solve the optimal or approximately optimal reconnaissance sequence.In the path smoothing module,the Dubins curve is applied to smooth the flight path,which assure the availability of the planned path.Furthermore,an online re-planning algorithm is designed for the uncertain factor that the UAV is damaged.Finally,reconnaissance planning and re-planning experiment results show that the algorithm proposed in this paper are effective and the algorithms designed for sequence planning have a great advantage in solving efficiency and optimality.展开更多
In order to realize the explorer autonomy, the software architecture of autonomous mission management system (AMMS) is given for the deep space explorer, and the autonomous mission planning system, the kernel part of ...In order to realize the explorer autonomy, the software architecture of autonomous mission management system (AMMS) is given for the deep space explorer, and the autonomous mission planning system, the kernel part of this architecture, is designed in detail. In order to describe the parallel activity, the state timeline is introduced to build the formal model of the planning system and based on this model, the temporal constraint satisfaction planning algorithm is proposed to produce the explorer’s activity sequence. With some key subsystems of the deep space explorer as examples, the autonomous mission planning simulation system is designed. The results show that this system can calculate the executable activity sequence with the given mission goals and initial state of the explorer.展开更多
Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system comp...Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.展开更多
Advanced countries around the world are spurring the development of Unmanned Surface Vehicles (USVs) that can operate autonomously at marine environment. The key enabling technology for such USVs is the mission planni...Advanced countries around the world are spurring the development of Unmanned Surface Vehicles (USVs) that can operate autonomously at marine environment. The key enabling technology for such USVs is the mission planning system (MPS) that can autonomously navigate through the harsh waters. The MPS not only has the functions for the navigation, but also has the capabilities, such as obstacle avoidance, malfunction corrections, dealing with unexpected events, return home functions, and many other eventualities that cannot be programmed in advance. The autonomy levels are increasingly moving higher and it is foreseeable that the trend will continue in the future. The main purpose of this paper is the analysis of the MPS onboard the USVs, in terms of the categories, functions, and technological details. Also, we analyze the case study of autonomous mission planning control systems in various fields and introduce the features that constitute the critical functionalities of the mission planning systems.展开更多
The integrated Mission Planning System?(MPS) of Unmanned Surface Vehicle?(USV) refers to the process which can recognize, decide, plan situations and carry out missions, such as human beings, for all incidental or com...The integrated Mission Planning System?(MPS) of Unmanned Surface Vehicle?(USV) refers to the process which can recognize, decide, plan situations and carry out missions, such as human beings, for all incidental or complex events occurring at sea. In the actual operating environment, it is necessary to develop a simulation software environment and analyze, verify it in advance so as to make an appropriate mission plan considering equipment, sensor, fuel, and other available resources. The existing USV mission planning process methodology has several limitations in the analysis of USV missions because the scenario to be tested is limited and autonomy of USV is not considered sufficiently. To overcome these problems, we constructed a process that considers various missions and is more autonomous, and an integrated environment in which to experiment. In this study, we designed a multi-agent based USV Integrated Mission Planning System and modeled each component. In addition, we constructed the USV remote operation S/W based on M&S that user can experiment with the modeled process and verified the usefulness of the developed system through simulations.展开更多
Unmanned aerial vehicles(UAVs)are increasingly applied in various mission scenarios for their versatility,scalability and cost-effectiveness.In UAV mission planning systems(UMPSs),an efficient mission planning strateg...Unmanned aerial vehicles(UAVs)are increasingly applied in various mission scenarios for their versatility,scalability and cost-effectiveness.In UAV mission planning systems(UMPSs),an efficient mission planning strategy is essential to meet the requirements of UAV missions.However,rapidly changing environments and unforeseen threats pose challenges to UMPSs,making efficient mission planning difficult.To address these challenges,knowledge graph technology can be utilized to manage the complex relations and constraints among UAVs,missions,and environments.This paper investigates knowledge graph application in UMPSs,exploring its modeling,representation,and storage concepts and methodologies.Subsequently,the construction of a specialized knowledge graph for UMPS is detailed.Furthermore,the paper delves into knowledge reasoning within UMPSs,emphasizing its significance in timely updates in the dynamic environment.A graph neural network(GNN)-based approach is proposed for knowledge reasoning,leveraging GNNs to capture structural information and accurately predict missing entities or relations in the knowledge graph.For relation reasoning,path information is also incorporated to improve the accuracy of inference.To account for the temporal dynamics of the environment in UMPS,the influence of timestamps is captured through the attention mechanism.The effectiveness and applicability of the proposed knowledge reasoning method are verified via simulations.展开更多
Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mi...Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mission and route planning for a fleet of UAVs. The mission planning determines the configuration of weapons in UAVs and the weapons to attack targets, while the route planning determines the UAV’s visiting sequence for the targets. The problem is formulated as an integer linear programming model. Due to the inefficiency of CPLEX on large scale optimization problems, an effective learningbased heuristic, namely, population based adaptive large neighborhood search(P-ALNS), is proposed to solve the model. In P-ALNS, seven neighborhood structures are designed and adaptively utilized in terms of their historical performance. The effectiveness and superiority of the proposed model and algorithm are demonstrated on test instances of small, medium and large sizes. In particular, P-ALNS achieves comparable solutions or as good as those of CPLEX on small-size(20 targets)instances in much shorter time.展开更多
This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning(DISOMP)algorithm for multiple Unmanned Aerial...This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning(DISOMP)algorithm for multiple Unmanned Aerial Vehicles(multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization(ACO) algorithm, an attack module designed based on the Parallel Approach(PA)scheme, a threat avoidance module designed based on the Dubins Curve(DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.展开更多
This study concentrates of the new generation of the agile (AEOS). AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satell...This study concentrates of the new generation of the agile (AEOS). AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.展开更多
A spatial orthogonal allocation method is devised for multirobot tasks allocation.A 3D space model is adopted to describe exploration mission;meanwhile spatial orthogonal tentative technology is utilized to update the...A spatial orthogonal allocation method is devised for multirobot tasks allocation.A 3D space model is adopted to describe exploration mission;meanwhile spatial orthogonal tentative technology is utilized to update the attractor position for load balance.Heterogeneous interactive cultural hybrid architecture is proposed to solve a robot route planning problem;it utilizes good-point-set to initialize population spaces,redefine novel evolution model and particle evolution ability,and introduce near-neighbor local search strategy in order to enhance search capability.Finally,spatial orthogonal allocation and heterogeneous cultural hybrid algorithm (SOAHCHA) are verified by simulation analysis and MORCS2 planning experiments;those results show that the proposed algorithm is efficient because of its successful performance and balanced allocation.展开更多
The scale expansion of the space information networks(SINs)makes the demands for tacking,telemetry and command(TT&C)missions increase dramatically.An increasing number of missions and a sharp conflict of resources...The scale expansion of the space information networks(SINs)makes the demands for tacking,telemetry and command(TT&C)missions increase dramatically.An increasing number of missions and a sharp conflict of resources make it much more challenging to schedule missions reasonably.In order to ensure both the mission completion rate of the high concurrent emergency missions and the performance of regular missions,a conflict degree scheduling algorithm based on transfer strategy(CDSA-TS)is proposed concurrently reconfiguring multi-dimensional resources reasonably.Furthermore,we design an emergency mission planning algorithm based on simulated annealing algorithm(EMPA-SA)to increase the probability of jumping out of the trap through the iterative neighborhood searching strategy and destabilization.Finally,we design a simulation system to verify the network performance in terms of the integrated weights of completed missions and the time consumption of the proposed algorithms.We also investigate the impact of the scheduling strategy for emergency missions on regular missions to improve the overall network performance,which provides guidance for emergency mission planning in the future for the large scale constellation oriented SINs.展开更多
Multi-robot mission planning is composed of assignment allocation and mobile-robot route planning in this paper.Multi-robot exploration missions adopts fuzzy c-mean(FCM)algorithm to allocate,and then,heterogeneous int...Multi-robot mission planning is composed of assignment allocation and mobile-robot route planning in this paper.Multi-robot exploration missions adopts fuzzy c-mean(FCM)algorithm to allocate,and then,heterogeneous interactive cultural hybrid algorithm(HICHA)is devised for route planning in order to optimize mobilerobot execution path.Meanwhile,we design multi-robot mission replanning mechanism based on the rules system of greedy algorithm for dynamic stochastic increment missions.Finally,extensive simulation experiments were shown that FCM for assignment allocation and HICHA for route planning were efficacious for mobile-robot exploration mission planning.Furthermore,the improved greedy algorithm based on experience rules met dynamic stochastic increment missions replanning requirement for load balance.展开更多
High-level efficiency and safety are of great significance for improving the fighting capability of an aircraft carrier. One way to enhance efficiency and safety level is to organize the carrier aircraft into combat e...High-level efficiency and safety are of great significance for improving the fighting capability of an aircraft carrier. One way to enhance efficiency and safety level is to organize the carrier aircraft into combat effectively. This paper studies the mission planning problem for a team of carrier aircraft launching, and a novel distributed mission planning architecture is proposed. The architecture is hierarchical and is comprised of four levels, namely, the input level, the coordination level,the path planning level and the execution level. Realistic constraints in each level of the distributed architecture, such as the vortex flow effect, the crowd effect and the motion of aircraft, are considered in the model. To solve this problem, a distributed path planning algorithm based on the asynchronous planning strategy is developed. The proposed Mission Planning Approach for Carrier Aircraft Launching(MPACAL) is validated using the setups of the Nimitz-class aircraft carrier.Compared to the isolated planning architecture and the centralized planning architecture, the proposed distributed planning architecture has advantages in coordinating the launch tasks not only belonging to the same catapult but also when all different catapults are considered. The proposed MPACAL provides a modeling method for the flight deck operation on aircraft carrier.展开更多
This paper studies the multi-objective optimization of space station short-term mission planning(STMP), which aims to obtain a mission-execution plan satisfying multiple planning demands. The planning needs to allocat...This paper studies the multi-objective optimization of space station short-term mission planning(STMP), which aims to obtain a mission-execution plan satisfying multiple planning demands. The planning needs to allocate the execution time effectively, schedule the on-board astronauts properly, and arrange the devices reasonably. The STMP concept models for problem definitions and descriptions are presented, and then an STMP multi-objective planning model is developed. To optimize the STMP problem, a Non-dominated Sorting Genetic Algorithm II(NSGA-II) is adopted and then improved by incorporating an iterative conflict-repair strategy based on domain knowledge. The proposed approach is demonstrated by using a test case with thirty-five missions, eighteen devices and three astronauts. The results show that the established STMP model is effective, and the improved NSGA-II can successfully obtain the multi-objective optimal plans satisfying all constraints considered. Moreover, through contrast tests on solving the STMP problem, the NSGA-II shows a very competitive performance with respect to the Strength Pareto Evolutionary Algorithm II(SPEA-II) and the Multi-objective Particle Swarm Optimization(MOPSO).展开更多
文摘Space emergency launching is to send a satellite into space by using a rapid responsive solid rocket in the bounded time to implement the emergency Earth observation mission.The key and difficult points mainly include the business process construction of launching mission planning,validation of the effectiveness of the launching scheme,etc.This paper pro-poses the agile space emergency launching mission planning simulation and verification method,which systematically con-structs the overall technical framework of space emergency launching mission planning with multi-field area,multi-platform and multi-task parallel under the constraint of resource schedul-ing for the first time.It supports flexible reconstruction of mis-sion planning processes such as launching target planning,tra-jectory planning,path planning,action planning and launching time analysis,and can realize on-demand assembly of operation links under different mission scenarios and different plan condi-tions,so as to quickly modify and generate launching schemes.It supports the fast solution of rocket trajectory data and the accurate analysis of multi-point salvo time window recheck and can realize the fast conflict resolution of launching missions in the dimensions of launching position and launching window sequence.It supports lightweight scenario design,modular flexi-ble simulation,based on launching style,launching platform,launching rules,etc.,can realize the independent mapping of mission planning results to two-dimensional and three-dimen-sional visual simulation models,so as to achieve a smooth con-nection between mission planning and simulation.
基金supported by the National Natural Science Foundation of China(61502534)the Shaanxi Provincial Natural Science Foundation(2020JQ-493)+2 种基金the Integrative Equipment Research Project of Armed Police Force(WJ20211A030018)the Military Science Project of the National Social Science Fund(WJ2019-SKJJ-C-092)the Theoretical Research Foundation of Armed Police Engineering University(WJY202148)。
文摘Cooperative search-attack is an important application of unmanned aerial vehicle(UAV)swarm in military field.The coupling between path planning and task allocation,the heterogeneity of UAVs,and the dynamic nature of task environment greatly increase the complexity and difficulty of the UAV swarm cooperative search-attack mission planning problem.Inspired by the collaborative hunting behavior of wolf pack,a distributed selforganizing method for UAV swarm search-attack mission planning is proposed.First,to solve the multi-target search problem in unknown environments,a wolf scouting behavior-inspired cooperative search algorithm for UAV swarm is designed.Second,a distributed self-organizing task allocation algorithm for UAV swarm cooperative attacking of targets is proposed by analyzing the flexible labor division behavior of wolves.By abstracting the UAV as a simple artificial wolf agent,the flexible motion planning and group task coordinating for UAV swarm can be realized by self-organizing.The effectiveness of the proposed method is verified by a set of simulation experiments,the stability and scalability are evaluated,and the integrated solution for the coupled path planning and task allocation problems for the UAV swarm cooperative search-attack task can be well performed.
基金Sponsored by the National Natural Science Foundation of China(Grant No.70601035 and 70801062)
文摘This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-strip area,real time download request,and stereoscopic request) and complex satellite actions,such as observe action and data download action,are considered in this paper. Through reasonable analysis of specialties and operational constraints of agile satellites in observing process,the mission scheduling model under multiple objective conditions is constructed. A genetic algorithm combined with heuristic rules is designed to solve problem. Genetic algorithm is designed to arrange user missions and heuristic rules are used to arrange satellite actions. Experiment results suggest that our algorithm works well for the agile Earth-observing satellite scheduling problem.
基金the National Key Research and Development Program of China(Grant No.2016YFB0500801)sponsored by Qing Lan Project.
文摘Satellite observation schedule is investigated in this paper.A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite.The newly developed method can make the satellite observe more targets and therefore save observation resources.First,for the densely distributed target points,a preprocessing scheme based on task clustering is proposed.The target points are clustered according to the distance condition.Second,the local observation path is generated by Tabu algorithm in the inner layer of cluster regions.Third,considering the scatter and cluster sets,the global observation path is obtained by adopting Tabu algorithm in the outer layer.Simulation results show that the algorithm can effectively reduce the task planning time of large-scale point targets while ensuring the optimal solution quality.
基金supported by the National Natural Science Foundation of China(11402295)the Science Project of National University of Defense Technology(JC14-01-05)the Hunan Provincial Natural Science Foundation of China(2015JJ3020)
文摘This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time of the astronauts properly. A domain model is developed by using the ontology theory to describe the concepts, constraints and relations of the planning domain formally, abstractly and normatively. A method based on time iteration is adopted to solve the short-term planning problem. Meanwhile, the resolving strategies are proposed to resolve different kinds of conflicts induced by the constraints of power, heat, resource, astronaut and relationship. The proposed approach is evaluated in a test case with fifteen missions, thirteen resources and three astronauts. The results show that the developed domain ontology model is reasonable, and the time iteration method using the proposed resolving strategies can successfully obtain the plan satisfying all considered constraints.
文摘Reconnaissance mission planning of multiple unmanned aerial vehicles(UAVs)under an adversarial environment is a discrete combinatorial optimization problem which is proved to be a non-deterministic polynomial(NP)-complete problem.The purpose of this study is to research intelligent multiUAVs reconnaissance mission planning and online re-planning algorithm under various constraints in mission areas.For numerous targets scattered in the wide area,a reconnaissance mission planning and re-planning system is established,which includes five modules,including intelligence analysis,sub-mission area division,mission sequence planning,path smoothing,and online re-planning.The intelligence analysis module depicts the attribute of targets and the heterogeneous characteristic of UAVs and computes the number of sub-mission areas on consideration of voyage distance constraints.In the sub-mission area division module,an improved K-means clustering algorithm is designed to divide the reconnaissance mission area into several sub-mission areas,and each sub-mission is detected by the UAV loaded with various detective sensors.To control reconnaissance cost,the sampling and iteration algorithms are proposed in the mission sequence planning module,which are utilized to solve the optimal or approximately optimal reconnaissance sequence.In the path smoothing module,the Dubins curve is applied to smooth the flight path,which assure the availability of the planned path.Furthermore,an online re-planning algorithm is designed for the uncertain factor that the UAV is damaged.Finally,reconnaissance planning and re-planning experiment results show that the algorithm proposed in this paper are effective and the algorithms designed for sequence planning have a great advantage in solving efficiency and optimality.
文摘In order to realize the explorer autonomy, the software architecture of autonomous mission management system (AMMS) is given for the deep space explorer, and the autonomous mission planning system, the kernel part of this architecture, is designed in detail. In order to describe the parallel activity, the state timeline is introduced to build the formal model of the planning system and based on this model, the temporal constraint satisfaction planning algorithm is proposed to produce the explorer’s activity sequence. With some key subsystems of the deep space explorer as examples, the autonomous mission planning simulation system is designed. The results show that this system can calculate the executable activity sequence with the given mission goals and initial state of the explorer.
基金Projects(61071096,61003233,61073103)supported by the National Natural Science Foundation of ChinaProjects(20100162110012,20110162110042)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.
文摘Advanced countries around the world are spurring the development of Unmanned Surface Vehicles (USVs) that can operate autonomously at marine environment. The key enabling technology for such USVs is the mission planning system (MPS) that can autonomously navigate through the harsh waters. The MPS not only has the functions for the navigation, but also has the capabilities, such as obstacle avoidance, malfunction corrections, dealing with unexpected events, return home functions, and many other eventualities that cannot be programmed in advance. The autonomy levels are increasingly moving higher and it is foreseeable that the trend will continue in the future. The main purpose of this paper is the analysis of the MPS onboard the USVs, in terms of the categories, functions, and technological details. Also, we analyze the case study of autonomous mission planning control systems in various fields and introduce the features that constitute the critical functionalities of the mission planning systems.
文摘The integrated Mission Planning System?(MPS) of Unmanned Surface Vehicle?(USV) refers to the process which can recognize, decide, plan situations and carry out missions, such as human beings, for all incidental or complex events occurring at sea. In the actual operating environment, it is necessary to develop a simulation software environment and analyze, verify it in advance so as to make an appropriate mission plan considering equipment, sensor, fuel, and other available resources. The existing USV mission planning process methodology has several limitations in the analysis of USV missions because the scenario to be tested is limited and autonomy of USV is not considered sufficiently. To overcome these problems, we constructed a process that considers various missions and is more autonomous, and an integrated environment in which to experiment. In this study, we designed a multi-agent based USV Integrated Mission Planning System and modeled each component. In addition, we constructed the USV remote operation S/W based on M&S that user can experiment with the modeled process and verified the usefulness of the developed system through simulations.
基金This work was supported in part by the National Natural Science Foundation of China(62271097,U23A20279).
文摘Unmanned aerial vehicles(UAVs)are increasingly applied in various mission scenarios for their versatility,scalability and cost-effectiveness.In UAV mission planning systems(UMPSs),an efficient mission planning strategy is essential to meet the requirements of UAV missions.However,rapidly changing environments and unforeseen threats pose challenges to UMPSs,making efficient mission planning difficult.To address these challenges,knowledge graph technology can be utilized to manage the complex relations and constraints among UAVs,missions,and environments.This paper investigates knowledge graph application in UMPSs,exploring its modeling,representation,and storage concepts and methodologies.Subsequently,the construction of a specialized knowledge graph for UMPS is detailed.Furthermore,the paper delves into knowledge reasoning within UMPSs,emphasizing its significance in timely updates in the dynamic environment.A graph neural network(GNN)-based approach is proposed for knowledge reasoning,leveraging GNNs to capture structural information and accurately predict missing entities or relations in the knowledge graph.For relation reasoning,path information is also incorporated to improve the accuracy of inference.To account for the temporal dynamics of the environment in UMPS,the influence of timestamps is captured through the attention mechanism.The effectiveness and applicability of the proposed knowledge reasoning method are verified via simulations.
基金supportes by the National Nature Science Foundation o f China (71771215,62122093)。
文摘Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mission and route planning for a fleet of UAVs. The mission planning determines the configuration of weapons in UAVs and the weapons to attack targets, while the route planning determines the UAV’s visiting sequence for the targets. The problem is formulated as an integer linear programming model. Due to the inefficiency of CPLEX on large scale optimization problems, an effective learningbased heuristic, namely, population based adaptive large neighborhood search(P-ALNS), is proposed to solve the model. In P-ALNS, seven neighborhood structures are designed and adaptively utilized in terms of their historical performance. The effectiveness and superiority of the proposed model and algorithm are demonstrated on test instances of small, medium and large sizes. In particular, P-ALNS achieves comparable solutions or as good as those of CPLEX on small-size(20 targets)instances in much shorter time.
基金supported in part by National Natural Science Foundation of China (Nos. 61741313, 61673209, and 61533008)Jiangsu Six Peak of Talents Program, China (No. KTHY-027)Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (No. KYCX18_0303)
文摘This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning(DISOMP)algorithm for multiple Unmanned Aerial Vehicles(multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization(ACO) algorithm, an attack module designed based on the Parallel Approach(PA)scheme, a threat avoidance module designed based on the Dubins Curve(DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.
基金supported by the National Natural Science Foundation of China(7127106671171065+1 种基金71202168)the Natural Science Foundation of Heilongjiang Province(GC13D506)
文摘This study concentrates of the new generation of the agile (AEOS). AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.
基金supported by the National Natural Science Foundation of China (No. 90820302)the Research Fund for the Doctoral Program of Higher Education (No. 200805330005)+1 种基金Hunan S & T Funds (No. 06IJY3035)the Postdoctoral Science Foundation of Central South University
文摘A spatial orthogonal allocation method is devised for multirobot tasks allocation.A 3D space model is adopted to describe exploration mission;meanwhile spatial orthogonal tentative technology is utilized to update the attractor position for load balance.Heterogeneous interactive cultural hybrid architecture is proposed to solve a robot route planning problem;it utilizes good-point-set to initialize population spaces,redefine novel evolution model and particle evolution ability,and introduce near-neighbor local search strategy in order to enhance search capability.Finally,spatial orthogonal allocation and heterogeneous cultural hybrid algorithm (SOAHCHA) are verified by simulation analysis and MORCS2 planning experiments;those results show that the proposed algorithm is efficient because of its successful performance and balanced allocation.
基金the Natural Science Foundation of China under Grant U19B2025 and Grant 62001347China Postdoctoral Science Foundation under Grant 2019TQ0241 and Grant 2020M673344the Fundamental Research Funds for the Central Universities under Grant XJS200117。
文摘The scale expansion of the space information networks(SINs)makes the demands for tacking,telemetry and command(TT&C)missions increase dramatically.An increasing number of missions and a sharp conflict of resources make it much more challenging to schedule missions reasonably.In order to ensure both the mission completion rate of the high concurrent emergency missions and the performance of regular missions,a conflict degree scheduling algorithm based on transfer strategy(CDSA-TS)is proposed concurrently reconfiguring multi-dimensional resources reasonably.Furthermore,we design an emergency mission planning algorithm based on simulated annealing algorithm(EMPA-SA)to increase the probability of jumping out of the trap through the iterative neighborhood searching strategy and destabilization.Finally,we design a simulation system to verify the network performance in terms of the integrated weights of completed missions and the time consumption of the proposed algorithms.We also investigate the impact of the scheduling strategy for emergency missions on regular missions to improve the overall network performance,which provides guidance for emergency mission planning in the future for the large scale constellation oriented SINs.
基金This work was supported in part by the National Natural Science Foundation of China(Grant No.90820302)the Research Fund for the Doctoral Program of Higher Education(No.200805330005)Hunan S&T Funds(No.06IJY3035).
文摘Multi-robot mission planning is composed of assignment allocation and mobile-robot route planning in this paper.Multi-robot exploration missions adopts fuzzy c-mean(FCM)algorithm to allocate,and then,heterogeneous interactive cultural hybrid algorithm(HICHA)is devised for route planning in order to optimize mobilerobot execution path.Meanwhile,we design multi-robot mission replanning mechanism based on the rules system of greedy algorithm for dynamic stochastic increment missions.Finally,extensive simulation experiments were shown that FCM for assignment allocation and HICHA for route planning were efficacious for mobile-robot exploration mission planning.Furthermore,the improved greedy algorithm based on experience rules met dynamic stochastic increment missions replanning requirement for load balance.
文摘High-level efficiency and safety are of great significance for improving the fighting capability of an aircraft carrier. One way to enhance efficiency and safety level is to organize the carrier aircraft into combat effectively. This paper studies the mission planning problem for a team of carrier aircraft launching, and a novel distributed mission planning architecture is proposed. The architecture is hierarchical and is comprised of four levels, namely, the input level, the coordination level,the path planning level and the execution level. Realistic constraints in each level of the distributed architecture, such as the vortex flow effect, the crowd effect and the motion of aircraft, are considered in the model. To solve this problem, a distributed path planning algorithm based on the asynchronous planning strategy is developed. The proposed Mission Planning Approach for Carrier Aircraft Launching(MPACAL) is validated using the setups of the Nimitz-class aircraft carrier.Compared to the isolated planning architecture and the centralized planning architecture, the proposed distributed planning architecture has advantages in coordinating the launch tasks not only belonging to the same catapult but also when all different catapults are considered. The proposed MPACAL provides a modeling method for the flight deck operation on aircraft carrier.
基金supported by the National Natural Science Foundation of China(Grant No.11402295)the Science Project of National University of Defense Technology(Grant No.JC14-01-05)the Hunan Provincial Natural Science Foundation of China(Grant No.2015JJ3020)
文摘This paper studies the multi-objective optimization of space station short-term mission planning(STMP), which aims to obtain a mission-execution plan satisfying multiple planning demands. The planning needs to allocate the execution time effectively, schedule the on-board astronauts properly, and arrange the devices reasonably. The STMP concept models for problem definitions and descriptions are presented, and then an STMP multi-objective planning model is developed. To optimize the STMP problem, a Non-dominated Sorting Genetic Algorithm II(NSGA-II) is adopted and then improved by incorporating an iterative conflict-repair strategy based on domain knowledge. The proposed approach is demonstrated by using a test case with thirty-five missions, eighteen devices and three astronauts. The results show that the established STMP model is effective, and the improved NSGA-II can successfully obtain the multi-objective optimal plans satisfying all constraints considered. Moreover, through contrast tests on solving the STMP problem, the NSGA-II shows a very competitive performance with respect to the Strength Pareto Evolutionary Algorithm II(SPEA-II) and the Multi-objective Particle Swarm Optimization(MOPSO).