Dynamic collaborative planning method of earth observation resources based on contract network
-
摘要:
卫星、无人机等对地观测资源已经成为执行灾害救援、灾损评估等多样化监测任务的主要观测手段，而大规模任务的随机调整和动态执行环境是快速制定对地观测方案的核心难点。针对此问题，提出一种面向不确定环境的对地观测资源动态协同规划方法，以动态高效地制定异构观测资源的协同观测方案。首先，结合合同网协议提出一种自下而上的分布式动态协同框架，以整合空天地异构观测资源构建分布式、动态、松耦合的协同观测网络。然后，根据该协同框架提出多轮组合分配方法及优化算法以快速动态地分配大规模监测任务。最后，通过仿真实验证明，在任务持续并发的动态不确定环境中，基于合同网的动态协同规划方法在提升了约25%任务完成率的同时，降低了约20%的运行时间，实现了任务完成率与方法运行时间的平衡。
Abstract:Satellite, UAV and other earth observation resources have become the main observation means to carry out various monitoring tasks, such as disaster rescue, disaster damage assessment, etc. Random adjustment and dynamic execution environment of large-scale tasks are the core problems to quickly develop earth observation programs. In view of the above problems, a dynamic collaborative planning method for earth observation resources in uncertain conditions is proposed to dynamically and efficiently develop the cooperative observation scheme of heterogeneous resources. First, a bottom-up distributed dynamic cooperative framework is proposed based on the contract network protocol to integrate the heterogeneous observation resources of air-space-ground and to build a distributed, dynamic and loosely coupled cooperative observation network. Then, based on the above collaborative framework, a multi-round combination allocation method and an optimization algorithm are proposed to allocate large-scale monitoring tasks rapidly and dynamically. Finally, the results of simulation experiment show that the dynamic collaborative planning method based on contract network improves the task completion rate by about 25% and reduces the collaborative planning time by about 20% in the dynamic uncertain conditions with continuous task concurrency, which achieves the balance between task completion efficiency and method running time.
-
图 1 分布式动态协同框架示意图
Figure 1. Schematic diagram of distributed dynamic collaborative framework
图 3 自下而上的对地观测资源动态协同规划流程示意图
Figure 3. Down-top flowchart for dynamic collaborative planning of earth observation resources
图 4 协同规划方法对比实验结果
Figure 4. Comparative experimental results of collaborative planning method
表 1 重规划仿真实验任务完成率
Table 1. Re-planning simulation experimental task completion rate
重规划
次数任务
添加量任务
总量任务完成率/% DDCP MCP BCP AUS SSA 1 40 80 97.5 100 85.0 61.3 77.5 2 46 126 94.4 98.4 84.9 61.1 74.6 3 33 159 88.7 93.1 74.8 63.5 64.8 4 37 196 85.2 89.8 69.9 54.6 59.7 5 40 236 83.9 89.4 69.9 48.3 54.2 6 42 278 80.2 85.3 68.0 43.2 50.0 
下载: 导出CSV
表 2 重规划仿真实验运行时间
Table 2. Re-planning simulation experimental task running time
重规划次数 运动时间/s DDCP MCP BCP AUS SSA 1 0.764 2.200 1.226 0.766 0.781 2 0.803 3.297 2.707 0.875 0.828 3 0.892 5.641 2.979 1.031 1.203 4 1.088 7.219 4.394 1.466 1.437 5 1.331 9.578 5.908 1.969 2.344 6 1.549 14.98 8.768 2.375 2.984
下载: 导出CSV
表 3 重规划仿真实验方案改变率
Table 3. Re-planning simulation experimental scheme change rate
重规划
次数任务
增长率方案改变率/% DDCP MCP BCP AUS SSA 1 1 29.5 41.2 41.3 35.5 46.9 2 0.575 21.8 36.3 37.3 27.7 40.3 3 0.261 19.1 32.4 28.9 28.2 25.7 4 0.232 15.6 25.6 18.4 20.0 20.6 5 0.204 10.6 17.5 16.9 13.6 15.8 6 0.177 8.5 13.5 14.4 10.9 10.8
下载: 导出CSV
-
[1] 李德仁.论空天地一体化对地观测网络[J].地球信息科学学报, 2012, 14(4):419-425.LI D R.On space-air-ground integrated earth observation network[J].Journal of Geo-information Science, 2012, 14(4):419-425(in Chinese). [2] 龚燃.美国商业对地观测数据政策发展综述[J].国际太空, 2016(5):24-27.GONG R.Overview of the development of U.S.commercial earth observation satellite data policy[J].Space International, 2016(5):24-27(in Chinese). [3] 郭建宁.促进国家对地观测体系顺利发展的思考[J].中国工程科学, 2006, 8(10):47-53.GUO J N.Considerations on promoting the smooth development of national land observation system[J].Strategic Study of CAE, 2006, 8(10):47-53(in Chinese). [4] 天地一体、统筹建设高分辨率对地观测系统初具规模[J]. 2017(10): 69-71.Integration of heaven and earth, overall construction of high-resolution earth observation system has taken shape[J].Defence Science & Technology Industry, 2017(10): 69-71(in Chinese). [5] 江建清, 伍国华, 朱晓敏.一种两阶段多平台对地观测资源匹配方法[J].科学技术与工程, 2012, 12(27):6984-6990.JIANG J Q, WU G H, ZHU X M.A two phase matching approach of multi-platform earth observing resource[J].Science Technology and Engineering, 2012, 12(27):6984-6990(in Chinese). [6] 李勤勇, 宋建功, 高世伟, 等.面向地震应急响应的松耦合研判模型管理机制[J].北京亚洲成人在线一二三四五六区学报, 2017, 43(4):720-730. doi: 10.13700/j.bh.1001-5965.2016.0312LI Q Y, SONG J G, GAO S W, et al.A loose-coupled mechanism of analysis model management for earthquake emergency response[J].Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(4):720-730(in Chinese). doi: 10.13700/j.bh.1001-5965.2016.0312 [7] 董云峰, 卫晓娜, 郝朝.引入多Agent协商的协同优化在卫星设计中的应用[J].北京亚洲成人在线一二三四五六区学报, 2016, 42(5):1055-1064. doi: 10.13700/j.bh.1001-5965.2015.0640DONG Y F, WEI X N, HAO C.A multi-Agent negotiation based collaborative optimization application in satellite design[J].Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(5):1055-1064(in Chinese). doi: 10.13700/j.bh.1001-5965.2015.0640 [8] 伍国华, 马满好, 王慧林, 等.基于任务聚类的多星观测调度方法[J].航空学报, 2011, 32(7):1275-1282.WU G H, MA M H, WANG H L, et al.Multi-satellite observation scheduling based on task clustering[J].Acta Aeronautica et Astronautica Sinica, 2011, 32(7):1275-1282(in Chinese). [9] VIRGINIE G, DANIEL V.Enumeration and interactive selection of efficient paths in a multiple criteria graph for scheduling an earth observing satellite[J].European Journal of Operational Research, 2002, 139(3):39-45. [10] BIANCHESSI N, CORDEAU J F, DESROSIERS J, et al.A heuristic for the multi-satellite, multi-orbit and multi-user management of earth observation satellites[J].European Journal of Operational Research, 2007, 177(2):750-762. [11] ZHANG D, GUO L, CAI B, et al.A hybrid discrete particle swarm optimization for satellite scheduling problem[C]//2011 IEEE International Conference on Intelligent Computing and Integrated Systems.Piscataway: IEEE Press, 2011: 78-82. [12] WU G, MA M, ZHU J, et al.Multi-satellite observation integrated scheduling method oriented to emergency tasks and common tasks[J].Journal of Systems Engineering and Electronics, 2012, 23(5):723-733. [13] MIAO H, TIAN Y C.Dynamic robot path planning using an enhanced simulated annealing approach[J].Applied Mathematics and Computation, 2013, 222:420-437. doi: 10.1016/j.amc.2013.07.022 [14] JEAN B, ABDESLEM B, ABDELHAMID B, et al.A new mixed-integer linear programming model for rescue path planning in uncertain adversarial environment[J].Computers and Operations Research, 2012, 39(12):3420-3430. [15] YU T Y, TANG J, BAI L.Collision avoidance for cooperative UAVs with rolling optimization algorithm based on predictive state space[J].Applied Sciences, 2017, 7(4):368-376. [16] 曾佳, 申功璋, 夏洁, 等.面向地面运动目标的无人机协同航迹规划[J].北京亚洲成人在线一二三四五六区学报, 2009, 35(7):887-890. http://bhxb.cqjj8.com/CN/Y2009/V35/I7/887ZENG J, SHEN G Z, XIA J, et al.Cooperative trajectory planning for UAV towards moving target aground[J].Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(7):887-890(in Chinese). http://bhxb.cqjj8.com/CN/Y2009/V35/I7/887 [17] 孙明君, 史建国.基于MAS的多无人机任务规划系统研究[J].微计算机信息, 2009, 25(33):45-47.SUN M J, SHI J G.Research on mission planning system of multiple unmanned aerial vehicle based on multi-agent system[J].Microcomputer Information, 2009, 25(33):45-47(in Chinese). [18] 杨晨, 张少卿, 孟光磊.多无人机协同任务规划研究[J].指挥与控制学报, 2018, 4(3):234-248.YANG C, ZHANG S Q, MENG G L.Multi-UAV cooperative mission planning[J].Journal of Command and Control, 2018, 4(3):234-248(in Chinese). [19] 贺川, 邱涤珊, 许光, 等.面向对地成像观测任务的高空飞艇应急调度[J].航空学报, 2012, 33(11):2082-2092.HANG C, QIU D S, XU G, et al.Emergency scheduling of earth-observing imaging tasks on high-altitude airships[J].Acta Aeronautica et Astronautica Sinica, 2012, 33(11):2082-2092(in Chinese). [20] SALHI S, WASSAN N, HAJARAT M.The fleet size and mix vehicle routing problem with backhauls:Formulation and set partitioning-based heuristics[J].Transportation Research Part E:Logistics and Transportation Review, 2013, 56:22-35. doi: 10.1016/j.tre.2013.05.005 [21] WU G, LIU J, MA M H, et al.A two-phase scheduling method with the consideration of task clustering for earth observing satellites[J].Computers and Operations Research, 2013, 40(7):1884-1894. doi: 10.1016/j.cor.2013.02.009 [22] 李军, 钟志农, 景宁, 等.异构MAS结构下的空天资源多阶段协同任务规划方法[J].航空学报, 2013, 34(7):1682-1697.LI J, ZHONG Z N, JING N, et al.Space-air resources multi-phase cooperation task planning approach based on heterogeneous MAS model[J].Acta Aeronautica et Astronautica Sinica, 2013, 34(7):1682-1697(in Chinese). [23] LI J, CHEN H, JING N.A data transmission scheduling algorithm for rapid-response earth-observing operations[J].Chinese Journal of Aeronautics, 2014, 27(2):349-364. [24] 梁星星.面向海上移动目标跟踪观测的空天协同任务规划研究[D].长沙: 国防科学技术大学, 2016.LIANG X X.Research on aerospace cooperative mission planning for continuation observation of maritime moving targets[D].Changsha: National University of Defense Technology, 2016(in Chinese). [25] 付强, 王刚, 肖金科, 等.空天高速飞行器多传感器协同跟踪任务规划研究[J].系统工程与电子技术, 2014, 36(10):2007-2012.FU Q, WANG G, XIAO J K, et al.Research on multi-sensor cooperative tracking of high-speed aerospace vehicle[J].Systems Engineering and Electronics, 2014, 36(10):2007-2012(in Chinese). [26] 梁星星, 修保新, 范长俊, 等.面向海上移动目标的空天协同连续观测模型[J].系统工程理论与实践, 2018, 38(1):229-240.LIANG X X, XIU B X, FAN C J, et al.The aerospace cooperative planning model for maritime moving target continuation observation.[J].Systems Engineering-Theory & Practice, 2018, 38(1):229-240(in Chinese). [27] 庞策, 单甘霖, 段修生.多传感器协同识别跟踪多目标管理方法研究[J].北京亚洲成人在线一二三四五六区学报, 2019, 45(8):1674-1680. doi: 10.13700/j.bh.1001-5965.2018.0612PANG C, SHAN G L, DUAN X S.Management method for multiple sensors' recognizing and tracking multiple targets cooperatively[J].Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(8):1674-1680(in Chinese). doi: 10.13700/j.bh.1001-5965.2018.0612 -
下载:
点击查看大图
计量
- 文章访问数: 762
- HTML全文浏览量: 171
- PDF下载量: 90
- 被引次数: 0
