多移动机器人任务分配的市场方法研究
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摘要
人类可以借助多移动机器人系统执行工农业生产、军事国防和科学研究等领域中许多单调、繁重、复杂或危险的任务,实现降低人类劳动强度、提高工作效率、避免人员伤亡以及扩展人类活动空间等目的。任务分配是有效利用多移动机器人系统资源以充分发挥系统效能优势的重要基础,其重要性程度随系统成员的功能差异性和任务的结构复杂性的增加而增加。最优任务分配是最大化多移动机器人系统效能的前提条件,但在大多数情况下最优任务分配算法的计算复杂度随问题规模的指数级增长,当任务分配问题存在显著的动态不确定性时多移动机器人系统实现最优任务分配将愈加困难,在可接受的时间内实现最优分配的任务规模非常有限。
基于市场交易机制的任务分配方法是一种具有良好鲁棒性、灵活性和可扩展性的任务分配方法,其最大优势在于适合动态不确定性环境下多移动机器人系统中各机器人分布地通过最大化个体效能实现最大化系统总效能的目的。本文研究多移动机器人系统协作任务的分布式市场分配方法,分别对多移动机器人系统的松散耦合任务分配、紧密耦合任务分配以及动态任务的重分配的市场方法进行研究,目的在于探索基于市场机制协调的多移动机器人系统提高分布式任务分配最优性和动态任务重分配效率的新方法。
(1)本文通过引入代价标示图方法可以比较直观地描述移动机器人依次执行多个任务所消耗的移动代价、操作代价以及完成任务的回报等指标值。通过引入能力向量可以简洁地描述机器人能力的类型和大小,也便于描述不同机器人的能力异构性和机器人对应用任务能力需求的满足性。
(2)分布式协调的多移动机器人系统中各机器人的协作行为具有显著的并发性,若系统不支持不同任务管理者并发协商任务分配,则全局任务分配的最优性和实时性会受到制约。给出了一种基于并发合同网协议的任务管理者招标和任务投标者投标的算法框架,并提出一种基于动态邻居集合的任务招标对象选择方法。并发的协商方法有利于提高任务分配的最优性,也利于减少实现任务分配消耗的协商时间。
(3)针对松散耦合任务分配提出了一种基于序贯单项任务拍卖和任务分组分配的分布式任务分配方法。任务分配过程被划分成两个阶段,第一个阶段采用序贯单项任务拍卖过程确定每个机器人对每个任务的投标值,第二个阶段采用多个移动吸引子根据第一个阶段获得的投标值确定任务的分组,任务管理者根据分组结果确定任务的最终分配。新的方法可以显著提高任务分配的最优性,但增加的任务管理者的计算代价仅仅是O(m3),通讯代价的增加量是O(n),其中m是任务数量,n是参与任务分配的机器人数量。
(4)需要多个机器人紧密协调的紧密耦合任务的分配可以划分成两个层次的分配,第一个层次的分配是指将需要多个机器人紧密协调执行的多个单机器人任务作为一个整体分配给某个机器人群组执行,第二个层次的分配是指将若干个存在严格的空间或时间约束性的单机器人任务分配给同一群组内不同的机器人执行。第一个层次的分配问题主要是为给定任务寻找最优的机器人联盟问题,第二个层次的分配问题主要是解决协作机器人执行任务的时序约束性问题。本文针对第一个层次的分配问题提出了一种基于二进制粒子群优化技术的单任务联盟生成算法,可以有效地为给定任务生成合适的机器人联盟。
(5)针对多移动机器人系统的任务重分配问题,本文提出了一种基于预测控制理论的动态性强度估计方法,提出一种基于效用值变化强度估计的任务拍卖策略和投标策略,系统采用新的任务重分配策略可以显著低减少系统重分配任务的通讯代价和计算代价。
Multiple mobile robot systems can be used to execute many stuffy, heavy, complex, and dangerous tasks instead of human being in many fields, such as industry autonomous production, national defense, and science research etc. Through using multiple mobile robot systems, the labors'work extensity can be lightened, the efficiency can be promoted, the casualty of human can be decreased, and the space that human being can be being is extended. Allocating tasks properly among the robots is the vital foundation to utilize the resources, and to exert the power of multiple mobile robot system. Task allocation is becoming more and more significant as the size of multi-robot system and the complexity of the global tasks increases. For any multi-robot system, optimizing the task allocation is a precondition to maximize the performance of the whole system. But in most of the cases, the computation complexity of any algorithm to optimizing task allocation is exponential to scale of the problem. Especially, as the task allocation problem is more dynamic and uncertain, it is more difficult for multiple mobile robot systems to allocation tasks within a reasonable time.
Market-based approach to task allocation is robust, flexible, and scalable. The most important advantage of market-based approach is that it is suitable for distributed coordinated multi-robot systems in dynamic, uncertain environments to maximize the performance of the whole system through maximizing the individual performance.This thesis addressed some market-based approaches to task allocation, such as loosely-coupled task allocation, tightly-coupled task allocation, and dynamic task reallocation. The purpose of research is to find some new methods to improve the optimization of task allocation and task reallocation.
(1) In order to prescribe the execution cost and the reward of a mobile robot that execute several tasks in turn, one kind of cost description graph was proposed. By using capability vector to show the kinds and magnitude of a robot's capability, it is very convenient to express the heterogeneousness of the system, and the requirement of given tasks.
(2) Concurrency is a notable characteristic of robots in distributed mobile robot team. The optimization of global task allocation is limited if the system restricts the robots to initiate task allocation negotiation concurrently. An auction algorithm and a biding algorithm were proposed based on the contract net confirmation protocol to implement concurrent task negotiation. A kind of dynamic neighbor set was presented to determine the potential bidders as well. The method is propitious to improve the optimization of task allocation and to reduce the time to negotiate.
(3) A method combining sequent single-task auction mechanism and task clustering mechanism was proposed to improve optimization of loosely-coupled task allocation of multiple mobile robot systems. The allocation process includes two phrases. The tasks were pre-assigned by sequent single-task auction in the first phrase. Then, the task manger clusters the pre-assigned tasks by using movable attractors to optimize the allocation. The proposed method needs more computation cost of O(m3) to cluster m tasks than traditional sequential single-task auction methods, and only add O(n) communication cost to the system consisting of n robots.
(4) As for tightly-coupled task allocation, it can be divided into two allocation level. The firs level is to find a group of robots to execute some tasks which demand several robots tightly coordinated. The second level is to allocation the tightly-coupled subtasks to robots within a group. The problem of the first level equals to find a robot coalition to execute some tightly-coupled subtasks as a whole. Robot coalition formation problem is only addressed in the chapter four. A particle swarm optimization algorithm was proposed to form an optimized robot coalition for a given task. The results of stimulated experiments verified the presented algorithm.
(5) In order to reduce the cost of computation and communication for multi-robot system to reallocate unfinished tasks in dynamic uncertain environments, a new method to estimate the dynamic extensity of the task utility value was developed based on predictive control theory. The new strategy reduces magnitude auction call and biding proposal according to simulation experiments.
基于市场交易机制的任务分配方法是一种具有良好鲁棒性、灵活性和可扩展性的任务分配方法,其最大优势在于适合动态不确定性环境下多移动机器人系统中各机器人分布地通过最大化个体效能实现最大化系统总效能的目的。本文研究多移动机器人系统协作任务的分布式市场分配方法,分别对多移动机器人系统的松散耦合任务分配、紧密耦合任务分配以及动态任务的重分配的市场方法进行研究,目的在于探索基于市场机制协调的多移动机器人系统提高分布式任务分配最优性和动态任务重分配效率的新方法。
(1)本文通过引入代价标示图方法可以比较直观地描述移动机器人依次执行多个任务所消耗的移动代价、操作代价以及完成任务的回报等指标值。通过引入能力向量可以简洁地描述机器人能力的类型和大小,也便于描述不同机器人的能力异构性和机器人对应用任务能力需求的满足性。
(2)分布式协调的多移动机器人系统中各机器人的协作行为具有显著的并发性,若系统不支持不同任务管理者并发协商任务分配,则全局任务分配的最优性和实时性会受到制约。给出了一种基于并发合同网协议的任务管理者招标和任务投标者投标的算法框架,并提出一种基于动态邻居集合的任务招标对象选择方法。并发的协商方法有利于提高任务分配的最优性,也利于减少实现任务分配消耗的协商时间。
(3)针对松散耦合任务分配提出了一种基于序贯单项任务拍卖和任务分组分配的分布式任务分配方法。任务分配过程被划分成两个阶段,第一个阶段采用序贯单项任务拍卖过程确定每个机器人对每个任务的投标值,第二个阶段采用多个移动吸引子根据第一个阶段获得的投标值确定任务的分组,任务管理者根据分组结果确定任务的最终分配。新的方法可以显著提高任务分配的最优性,但增加的任务管理者的计算代价仅仅是O(m3),通讯代价的增加量是O(n),其中m是任务数量,n是参与任务分配的机器人数量。
(4)需要多个机器人紧密协调的紧密耦合任务的分配可以划分成两个层次的分配,第一个层次的分配是指将需要多个机器人紧密协调执行的多个单机器人任务作为一个整体分配给某个机器人群组执行,第二个层次的分配是指将若干个存在严格的空间或时间约束性的单机器人任务分配给同一群组内不同的机器人执行。第一个层次的分配问题主要是为给定任务寻找最优的机器人联盟问题,第二个层次的分配问题主要是解决协作机器人执行任务的时序约束性问题。本文针对第一个层次的分配问题提出了一种基于二进制粒子群优化技术的单任务联盟生成算法,可以有效地为给定任务生成合适的机器人联盟。
(5)针对多移动机器人系统的任务重分配问题,本文提出了一种基于预测控制理论的动态性强度估计方法,提出一种基于效用值变化强度估计的任务拍卖策略和投标策略,系统采用新的任务重分配策略可以显著低减少系统重分配任务的通讯代价和计算代价。
Multiple mobile robot systems can be used to execute many stuffy, heavy, complex, and dangerous tasks instead of human being in many fields, such as industry autonomous production, national defense, and science research etc. Through using multiple mobile robot systems, the labors'work extensity can be lightened, the efficiency can be promoted, the casualty of human can be decreased, and the space that human being can be being is extended. Allocating tasks properly among the robots is the vital foundation to utilize the resources, and to exert the power of multiple mobile robot system. Task allocation is becoming more and more significant as the size of multi-robot system and the complexity of the global tasks increases. For any multi-robot system, optimizing the task allocation is a precondition to maximize the performance of the whole system. But in most of the cases, the computation complexity of any algorithm to optimizing task allocation is exponential to scale of the problem. Especially, as the task allocation problem is more dynamic and uncertain, it is more difficult for multiple mobile robot systems to allocation tasks within a reasonable time.
Market-based approach to task allocation is robust, flexible, and scalable. The most important advantage of market-based approach is that it is suitable for distributed coordinated multi-robot systems in dynamic, uncertain environments to maximize the performance of the whole system through maximizing the individual performance.This thesis addressed some market-based approaches to task allocation, such as loosely-coupled task allocation, tightly-coupled task allocation, and dynamic task reallocation. The purpose of research is to find some new methods to improve the optimization of task allocation and task reallocation.
(1) In order to prescribe the execution cost and the reward of a mobile robot that execute several tasks in turn, one kind of cost description graph was proposed. By using capability vector to show the kinds and magnitude of a robot's capability, it is very convenient to express the heterogeneousness of the system, and the requirement of given tasks.
(2) Concurrency is a notable characteristic of robots in distributed mobile robot team. The optimization of global task allocation is limited if the system restricts the robots to initiate task allocation negotiation concurrently. An auction algorithm and a biding algorithm were proposed based on the contract net confirmation protocol to implement concurrent task negotiation. A kind of dynamic neighbor set was presented to determine the potential bidders as well. The method is propitious to improve the optimization of task allocation and to reduce the time to negotiate.
(3) A method combining sequent single-task auction mechanism and task clustering mechanism was proposed to improve optimization of loosely-coupled task allocation of multiple mobile robot systems. The allocation process includes two phrases. The tasks were pre-assigned by sequent single-task auction in the first phrase. Then, the task manger clusters the pre-assigned tasks by using movable attractors to optimize the allocation. The proposed method needs more computation cost of O(m3) to cluster m tasks than traditional sequential single-task auction methods, and only add O(n) communication cost to the system consisting of n robots.
(4) As for tightly-coupled task allocation, it can be divided into two allocation level. The firs level is to find a group of robots to execute some tasks which demand several robots tightly coordinated. The second level is to allocation the tightly-coupled subtasks to robots within a group. The problem of the first level equals to find a robot coalition to execute some tightly-coupled subtasks as a whole. Robot coalition formation problem is only addressed in the chapter four. A particle swarm optimization algorithm was proposed to form an optimized robot coalition for a given task. The results of stimulated experiments verified the presented algorithm.
(5) In order to reduce the cost of computation and communication for multi-robot system to reallocate unfinished tasks in dynamic uncertain environments, a new method to estimate the dynamic extensity of the task utility value was developed based on predictive control theory. The new strategy reduces magnitude auction call and biding proposal according to simulation experiments.
引文
[1]蔡自兴.机器人学.北京：清华大学出版社,2000
[2]谭民,王硕,曹志强.多机器人系统.北京：清华大学出版社,2005
[3]美国国家航天局主页http://www.nasa.gov/topics/moonmars/index.html
[4]Saptharishi M,Spence O,Diehl C,et al.Distributed surveillance and reconnaissance using multiple autonomous ATVs:CyberScout.IEEE Transactions on Robotics and Automation. 2002,18(5):826-836
[5]Vidal R, Shakernia O,Kim H,et al.Probabilistic pursuit-evasion games:theory, implementation,and experimental evaluation.IEEE Transactions on Robotics and Automation.2002,18(5):662-669
[6]Trevai C, Ota Jun, Arai T.Multiple mobile robot surveillance in unknown environments. Advanced Robotics.2007,21 (7):729-749
[7]Stoeter S A, Rybski P E, Stubbs K N, et al.A robot team for surveillance tasks:Design and architecture.Robotics and Autonomous Systems.2002,40(2-3):173-183
[8]Fischer K,Miiller J P,Pischel M.Cooperative transportation scheduling:an application domain for DAI. Journal of Applied Artificial Intelligence,1995,9(10):1-33
[9]Nishi T, Ando M, Konishi M. Distributed route planning for multiple mobile robots using an augmented Lagrangian decomposition and coordination technique. IEEE Transactions on Robotics.2005,21(6):1191-1200
[10]Yongguo M,Yung-Hsiang L,Hu Y C,et al.Deployment of mobile robots with energy and timing constraints.IEEE Transactions on Robotics,2006,22(3):507-522
[11]Koes M,Nourbakhsh I,Sycara K.Constraint optimization coordination architecture for search and rescue robotics.In Proceedings of the IEEE International Conference on Robotics and Automation.Orlando,FL,USA. Piscataway,NJ,USA:IEEE.2006.3977-3982
[12]Burgard W, Moors M, Stachniss C, et al. Coordinated multi-robot exploration. IEEE Transactions on Robotics.2005,21(3):376-386
[13]李鹏,黄心汉,王敏.基于混合DSm模型的多机器人地图构建.计算机研究与发展,2009,46(1)：70-76
[14]王跃,谭民,景奉水,等.多机器人协调操作大型物体的运动学分析及应用.机器人,2002,24(5)：45 1-454
[15]周浦城,洪斌镕,蔡则苏.多机器人运动目标搜索策略研究.哈尔滨工业大学学报,2005,37(7)：879-882
[16]Fukuda T,Nakagawa S.A dynamically reconfigurable robotic system(concept of a system and optimal configurations).In Proceedings of International Conference on Industrial Electronics,Control,and Instrumentation,1987.588-595
[17]Asama H, Matsumoto A, Ishida Y.Design of an autonomous and distributed robot system: ACTRESS.In Proceedings of the IEEE/RSJ International Workshop on Intelligent Robots and Systems,1989.283-290
[18]Hackwood S, Beni G.Self-organization of sensors for swarm intelligence. In Proceedings of IEEE International Conference on Robotics and Automation,1992,819-829
[19]Parker L E.ALLIANCE:an architecture for fault tolerant multirobot cooperation.IEEE Transactions on Robotics and Automation.1998.14(2):220-240
[20]Alami R, Fleury S, Herrb M, et al. Multi-robot cooperation in the MARTHA project. IEEE Robotics & Automation Magazine,1998.36-47
[21]Dias M B.TraderBots:a new paradigm for robust and efficient multirobot coordination in dynamic environments [PhD Thesis].Carnegie Mellon University,2004
[22]苏丽颖,曹志强,王硕,等.多机器人对未知环境进行实时在线探测的一种方法.高技术通讯,2003,13(11)：56-60
[23]Jung B,Sukhatme G. Tracking targets using multiple robots:the effect of environment occlusion.Autonomous Robots,2002,13(3):191-205
[24]Simmons R,Singh S,Hershberger D,et al.First results in the coordination of heterogeneous robots for large-scale assembly.In Proceedings of the International Symposium on Experimental Robotics,Lecture Notes in Control and Information Sciences,2000.271:323-332
[25]王磊,唐华斌,孙增圻.多机器人系统形成联合协作的综合评价算法.清华大学学报(自然科学版).2005.45(4)：505-508
[26]Parker L E.Current research in multi-robot systems. Artificial Life Robotics,2003,7(1-2): 1-5
[27]范永,谭民MRCS中机器人控制体系框架结构.控制与决策,2000,15(3)：325-328
[28]孟宪松,刘建华,张铭钧.多水下机器人编队通信研究.中国造船,2007,48(4)：77-84
[29]陈卫东,席裕庚,顾冬雷,等.一个面向复杂任务的多机器人分布式协调系统.控制理论与应用,2002,19(4)：505-510
[30]刘传才,杨静宇,唐振民.多个自主机器人的协作策略研究.计算机学报,1998,21(10)：952-955
[31]吴智政,席裕庚.一种基于理性原则的多机器人协调控制.自动化学报,2000,26(4)：454-460
[32]蔡庆生,张波.一种基于Agent团队的强化学习模型与应用研究.计算机研究与发展,2000,37(9)：1087-1093
[33]顾国昌,仲宇,张汝波.一种新的多智能体强化学习算法及其在多机器人协作任务中的应用.机器人,2003,25(4)：344-349
[34]陈为雄,李振龙.基于BDI模型的多机器人智能体系统设计.机器人,2004,26(4)：310-313
[35]陈世明,方华京.大规模移动智能群体的建模及联合行为分析.控制与决策.2005,20(12)：1392-1396
[36]曾广周,杨公平,王晓琳.基于Agent能力自信度的任务分配问题研究.计算机学报,2007,30(11)：1922-1929
[37]丁滢颍,何衍,蒋静坪.基于蚁群算法的多机器人协作策略.机器人,2003,25(5)：414-418
[38]宋梅萍,顾国昌,张汝波.多移动机器人协作任务的分布式控制系统.机器人,2003,25(5)：456-460
[39]CAO Zhi-Qiang,ZHANG Bin,WANG Shuo,et al.Cooperative hunting of multiple mobile robots in an unknown environment自动化学报,2003,29(4)：536-543
[40]苏治宝,陆际联,童亮.一种多移动机器人协作围捕策略.北京理工大学学报,2004,24(5)：403-406
[41]Cao Y U, Fukunaga A S, Kahng A B, et al. Cooperative mobile robotics:antecedents and directions. Autonomous Robots,1997,4(1):1-23
[42]Farinelli A, Iocchi L, Nardi D. Multirobot systems:a classification focused on coordination. IEEE Transactions on Systems,Man,and Cybernetics, Part B:Cybernetics. 2004,34(5):2015-2128
[43]Parker L E.Distributed intelligence:overview of the field and its application in multi-robot systems. Journal of Physical Agents,2008,2(1):5-14
[44]Breed M D, Robinson G E, Page R E. Division of labor during honey bee colony defense. Behavioral Ecology and Sociobiology.1990,27(6):395-401
[45]Mataric M J. Designing emergent behaviors:from local interactions to collective intelligence. In:Meyer J A, Roitblat H, Wilson S (eds.).In Proceedings of the International Conference on Simulation of Adaptive Behavior:From Animals to Animats. USA:MIT Press.1992.(2):432-441
[46]Arkin R C.Cooperation without communication:multiagent schema-based robot navigation.Journal of robotic systems.1992,9(3):351-364
[47]Gordon D M.The organization of work in social insect colonies.Nature,1996,380: 121-124
[48]Krieger M, Billeter J B, Keller L.Ant-like task allocation and recruitment in cooperative robots.Nature.2000,406:992-996
[49]Labella T H, Dorigo M, Deneubourg J L.Division of Labor in a group of robots inspired by ants'foraging behavior.ACM Transactions on Autonomous and Adaptive Systems. 2006,1(1):4-25
[50]Chien S,Barrett A,Estlin T,et al.A comparison of coordinated planning methods for cooperating rovers.In Proceedings of the Fourth International Conference on Autonomous Agents,2000.100-101
[51]Gerkey B P, Mataric M J.et al.A framework for studying multi-robot task allocation. In Proceedings of Multi-Robot Systems:From Swarms to Intelligent Automata. Netherlands. Kluwer Academic Publishers.2003.2:15-26
[52]Howard A,Parker L E,Sukhatme G S.Experiments with a large heterogeneous mobile robot team:exploration,mapping,deployment and detection. International Journal of Robotics Research,2006,25(5-6):431-447
[53]Parker L E. Multiple mobile robot systems. Siciliano B, et al.(eds). Handbook of Robotics, Springer.2008.921-941
[54]Dias M B, Stentz A. A comparative study between centralized market-based and behavioral multi-robot coordination approaches. In Proceedings of the 2003 IEEE/RSJ International Conference Intelligent Robots and Systems, Las Vegas, Nevada.2003. 2279-2284
[55]Wooldridge M(英国).多Agent系统引论(石纯一,张伟,徐晋晖,等译).北京：电子工业出版社,2003,134-156
[56]堵丁柱,葛可一,王洁.计算复杂性导论.北京：高等教育出版社,2002.35-60
[57]Sandholm T. An implementation of the Contract Net Protocol based on marginal cost calculations. In Proceedings of the National Conference on Artificial Intelligence, Washington,D.C.1993.256-262
[58]Mataric M J. Issues and approaches in design of collective autonomous agents. Robotics and Autonomous Systems.1995.16(2-4):321-331
[59]Baghaei K, Agah A.Task allocation and communication methodologies for multi-robot systems.Intelligent Automation and Soft Computing,2003,9(4):217-226
[60]原魁,李园,房立新.多移动机器人系统研究发展近况.自动化学报.2007,33(8)：785-794
[61]Choudhury B B, Biswal B B. Task allocation methodologies for multi-robot systems. In Proceeding of the IEEE Sponsored Conference on Computational Intelligence, Control and Computer Vision in Robotics & Automation, NIT Rourkela.2008.99-106
[62]张嵛,刘淑华.多机器人任务分配的研究与进展.智能系统学报,2008,3(2)：1 15-120
[63]黎萍,杨宜民.多机器人系统任务分配的研究进展.计算机工程与应用,2008,44(17)：201-205
[64]Brumitt B L, Stentz A. Dynamic mission planning for multiple mobile robots. In Proceedings of IEEE International Conference on Robotics and Automation, Minneapolis, MN, USA.1996.(3):2396-2401
[65]Huntsberger T, Pirjanian P, Trebi-Ollennu A, et al. CAMPOUT:a control architecture for tightly coupled coordination of multirobot systems for planetary surface exploration. IEEE Transactions on Systems, Man, and Cybernetics-Part A:Systems and Humans.2003. 33(5):550-559
[66]Zhu A, Yang S X. A neural network approach to dynamic task assignment of multirobots. IEEE Transactions on Neural Network.2006.17(5):1278-1287
[67]黄宛宁,龚建伟,王鹏辉.基于改进遗传算法的多机器人任务分配方法.计算机仿真,2006,23(11)：164-168
[68]姜健,臧希喆,闫继宏,等.基于一种蚁群算法的多机器人动态感知任务分配.机器人,2008,30(3)：254-258
[69]余伶俐,蔡自兴.基于当代学习离散粒子群算法的多机器人任务分配.计算机应用研究,2009,26(5)：1691-1694
[70]Chaimowicz L, Campos M, Kumar V. Dynamic role assignment for cooperative robots. In Proceedings of 2002 IEEE International Conference on Robotics and Automation, Washington, DC, United states. USA:Institute of Electrical and Electronics Engineers Inc.2002.1:293-298
[71]Koes M,Nourbakhsh I,Sycara K.Constraint optimization coordination architecture for search and rescue robotics.In Proceedings of the IEEE International Conference on Robotics and Automation.Orlando,FL,USA. Piscataway,NJ,USA:IEEE.2006.3977-3982
[72]Koes M, Sycara K, Nourbakhsh I. A constraint optimization framework for fractured robot teams. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems.2006.491-493
[73]董胜龙,席裕庚,陈卫东.多机器人不确定协作任务的动态优化方法.机器人,2002,24(1)：31-34
[74]Gao Yunyuan, Wei Wei. Multi-robot autonomous cooperation integrated with immune based dynamic task allocation. In Proceedings of ISDA 2006:Sixth International Conference on Intelligent Systems Design and Applications. Jinan, China.2006.2: 586-591
[75]陈余庆,庄严,王伟.基于Petri网的多机器人协作任务分配与导航研究.大连理工大学学报,2008,48(4)：602-606
[76]Murhpy R,Lisetti C,Tardif R,et al.Emotion-based control of cooperating heterogeneous mobile robots.IEEE Transactions on Robotics and Automation,2002,18(5):744-757
[77]褚海涛,洪炳镕.nulti robots cooperative based on action selection level软件学报,2002,13(9)：1773-1778
[78]Simmons R, Apfelbaum D, Fox D, et al. Coordinated deployment of multiple heterogeneous robots. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS),2000.2254-2260
[79]Werger B, Mataric M J. Broadcast of local eligibility for multi-target observation. In: Parker L E, Bekey G, Barhen J (eds), Distributed autonomous Robotic Systems 4, New York:Springer-Verlag.2000.347-356
[80]姜健,闫继宏,臧希喆,等.基于信息素的多机器人协作任务分配.计算机工程与应用,2008,44(2)：20-22
[81]Dias M B, Zlot R, Kalra N, et al. Market-based multirobot coordination:a survey and analysis. In Proceedings of IEEE. Piscataway, NJ, USA:IEEE.2006.94(7):1257-1270
[82]张飞,陈卫东,席裕庚.多机器人协作探索的改进市场法.控制与决策,2005,20(5)：516-520
[83]Dias M. B, Stenz A. A free market architecture for distributed control of a multirobot system. In Proceedings of the 6th International Conference on Intelligent Autonomous Systems(IAS-6).2000.115-122
[84]Guerrero J, Oliver G. Physical interference impact in multi-robot task allocation auction methods. In Proceedings of the IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications, IEEE Computer Society,Washington, DC, USA.2006.19-24
[85]Scerri P, Farinelli A, Okamoto S. Allocating tasks in extreme teams. In Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, ACM New York,NY,USA.2005.727-734
[86]Botelho S C, Alami R. M+:A scheme for multi-robot cooperation through negotiated task allocation and achievement. In Proceedings of the 1999 IEEE International Conference on Robotics & Automation,Michigan,USA.1999.1234-1239
[87]Gerkey B P, Mataric M J. Sold!:auction methods for multi-robot coordination, IEEE Transactions on Robotics and Automation.2002.18(5):758-768
[88]Sariel S, Balch T, Erdogan N. Naval mine countermeasure missions. IEEE Robotics &
Automation Magazine.2008.15(1):45-52
[89]Zhou Pu-Cheng,Han Yu-Sheng,Xue Mo-Gen.Extended contract net protocol for multi-robot dynamic task allocation.Information Technology Journal,2007.6(5):733-738
[90]龙涛,沈林成,朱华勇,等.面向协同任务的多UCAV分布式任务分配与协调技术自动化学报,2007,33(7)：73 1-737
[91]Gong Jian-wei,Huang wan-ning,Xiong Guang-ming,et al. Genetic algorithm based combinatorial auction method for multi-robot task allocation.Journal of Beijing Institute of Technology,2007.16(2):151-156
[92]姜健,臧希喆,赵杰.基于焦虑概念和拍卖方法的多机器人协作搜集.控制与决策,2008,23(5)：541-545
[93]范永,谭民MRCS中机器人控制体系框架结构.控制与决策,2000,15(3)：325-328
[94]柳林,季秀才,郑志强.基于市场法及能力分类的多机器人任务分配方法.机器人,2006,28(3)：337-343
[95]Liu Lin, Zheng Zhiqiang. Combinatorial bids based multi-robot task allocation, In Proceedings of International Conference on Robotics and Automation, Barcelona,Spain, 2005.1145-1150
[96]Bertsekas D P. The auction algorithm for assignment and other network flow problem. Massachusetts Institute of Technology, Laboratory for Information and Decision Systems.1989.1908:15-17
[97]Chien S, Barrett A, Estlin T, et al. A comparison of coordinated planning methods for cooperating rovers.In Proceedings of the Fourth International Conference on Autonomous Agents, Barcelona, Spain.2000.100-101
[98]Cheng-Heng Fua,Shuzhi Sam Ge.COBOS:cooperative back off adaptive scheme for multi-robot task allocation.IEEE Transactions on Robotics.2005.21(6):1168-1178
[99]Zhang Dandan, Xie Guangming, Yu Junzhi, et al. Adaptive task assignment for multiple mobile robots via swarm intelligence approach. Robotics and Autonomous Systems, 2007,55(7):572-588
[100]王进戈,王强.基于模糊评判的机器人足球比赛策略研究.哈尔滨工业大学学报,2005,37(7)：943-946
[101]Gage A.Multi-robot task allocation using affect.[PhD Thesis],University of South Florida,2004
[102]Hanna H. Decentralized approach for multi-robot task allocation problem with uncertain task execution.In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2005),2005.535-540
[103]Tang F, Parker L E. A complete methodology for generating multi-robot task solutions using asymtred and market-based task allocation. In Proceedings of IEEE International Conference on Robotics and Automation (ICRA).2007.3351-3358
[104]Modi P J,Jung H,Tambe M,et al.Dynamic distributed resource allocation:a distributed constraint satisfaction approach.Lecture Notes in Computer Science,Intelligent Agents VIII,Springer Berlin,Heidelberg,2002,264-276
[105]Lagoudakis M G,Berhault M,Koenig S,et al.Simple auctions with performance guarantees for multi-robot task allocation.In Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).Piscataway, NJ,USA:IEEE.2004.1: 698-705
[106]Korte,Bernhard.Combinatorial optimization:theory and algorithms.Berlin, New York: Springer,2006
[107]刘任任,郑瑾.离散数学.长沙：中南大学出版社,2005
[108]Dudek G, Jenkin M, Milios E, et al. Taxonomy for multi-agent robotics.Autonomous Robots,1996.3(4):375-397
[109]Freedman P.Time,Petri Nets,and robotics.IEEE Transactions on Robotics and Automation, 1991.7(4):417-433
[110]Zlot R, Stentz A. Market-based multirobot coordination for complex tasks. International Journal of Robotics Research.2006.25(1):73-101
[111]Ghallab M(法),Nau D(美),Traverso P(意).自动规划-理论与实践(姜云飞,杨强,译).北京：清华大学出版社.2008
[112]Godwin M F,Spry S,Hedrick J K.Distributed collaboration with limited communication using mission state estimates. In Proceedings of 2006 American Control Conference. Piscataway,NJ,USA:IEEE.2006.14-16
[113]张铃,张钹.问题求解理论及应用-商空间粒度计算理论及应用(第2版).北京：清华大学出版社,2007
[114]Kara I, Bektas T. Integer linear programming formulations of multiple salesman problems and its variations. European Journal of Operational Research,2006.174(3): 1449-1458
[115]Pagello E, D'Angelo A, Menegatti E. Cooperation issues and distributed sensing for multirobot systems.In Proceedings of the IEEE. USA:Institute of Electrical and Electronics Engineers Inc.2006.94(7):1370-1383
[116]Pongpunwattana A,Rysdyk R.Real-time planning for multiple autonomous vehicles in dynamic uncertain environments.Journal of Aerospace Computing, Information,and
Communication,2004.1(12):580-604
[117]Vig L,Adams J A.Multi-robot coalition formation.IEEE Transactions on Robotics.2006. 22(4):637-649
[118]Kagel J H,Levin D共同价值拍卖与赢者灾难.董保民,王勇等译.北京：中国人民大学出版社,2007
[119]Smith R G. The contract net protocol:high-level communication and control in a distributed Problem Solver. IEEE Transactions on.Computers.1980. C-29(12): 1104-1113
[120]Sandholm T. Contract types for satisficing task allocation:Ⅰ theoretical results. AAAI 1998 Spring Symposium:Satisficing Models, Stanford University, California.1998.68-75
[121]Sandholm T S, Lesser V R. Advantages of a leveled commitment contracting protocol. Technical Report:UM-CS-1995-072, University of Massachusetts Amherst,MA,USA. 1995
[122]Excelente-Toledo C, Bourne R, Jennings N. Reasoning about commitments and penalties for coordination between autonomous agents. In Proceedings of the fifth international conference on Autonomous agents, Montreal, Quebec, Canada.2001.131-138
[123]Aknine S, Pinson S, Shakun M F. An extended multi-agent negotiation protocol. Autonomous Agents and Multi-Agent Systems,2004.8(1):5-45
[124]Xu Y, Scerri P, Sycara K, Lewis M. Comparing market and token-based coordination. In Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems. Hakodate, Japan.2006.1113-1115
[125]Knabe T,Schillo M,Fischer K.Improvements to the FIPA Contract Net Protocol for performance increase and cascading applications.In International Workshop for Multi-Agent Interoperability at the German Conference on AI,2002,http://citeseerx.ist. psu.edu/viewdoc/summary?doi= 10.1.1.19.9772
[126]宋海刚,陈学广.合同网协议中的Agent可用度研究.计算机科学,2004,31(8)：127-129
[127]万武南,王晓京,宋春雨等.基于范例推理的合同网模型.小型微型计算机系统,2005,26(9)：1578-1581
[128]Deshpande U, Gupta A, Basu A. Performance enhancement of a contract net protocol based system through instance-based learning. IEEE Transactions on Systems, Man, and Cybernetics-part B:Cybernetics.2005.35(2):345-358
[129]Parker L E. Lifelong adaptation in heterogeneous multi-robot teams:response to continual variation in individual robot performance. Autonomous Robots,2000.8(3): 239-267
[130]Sandholm T,Suri S.BOB:Improved winner determination in combinatorial auctions and generalizations.Artificial Intelligence,2003,145:33-58
[131]Lagoudakis M, Markakis V, Kempe D, et al.Auction-Based Multi-Robot Routing.In Proceedings of the International Conference on Robotics:Science and Systems,2005. 343-350
[132]Koenig S, Tovey C, Lagoudakis M, et al. The power of sequential single-item auction for agent coordination. In Proceedings of the Twenty-First National Conference on Artificial Intelligence(AAAI-06).Boston,MA,USA.2007.2:1625-1629
[133]Andersson M, Sandholm T.Time-quality tradeoffs in reallocative negotiation with combinatorial contract types. In Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference.Orlando, Florida, USA.1999.3-10
[134]Berhault M, Huang H, Keskinocal P, et al. Robot exploration with combinatorial auctions. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.2003.2:1957-1962
[135]Surmann H,Morales A.Scheduling tasks to a team of autonomous mobile service robots in indoor environments.Journal of universal computer science,2002,8(8):809-833
[136]王树禾.图论.北京：科学出版社,2004
[137]Leung Yiu-Wing,Yuping Wang.An orthogonal genetic algorithm with quantization for global numerical optimization.IEEE Transactions on Evolutionary Computation,2001, 5(1):41-53
[138]史奎凡,董吉文,李金屏,等.正交遗传算法.电子学报,2002,30(10)：1501-1504
[139]杨子胥.正交表的构造.济南：山东人民出版社,1978.110-181
[140]http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsplib.html
[141]Ralphs T.Vehicle Routing Data Sets.http://www.coin-or.org/SYMPHONY/branchandcut/ VRP/data/#A, maintained by Ted Ralphs,2008
[142]高平安,蔡自兴.多移动机器人任务负载均衡分组规划算法法.高技术通讯,2009,19(5)：501-505
[143]Yongguo M, Yung-Hsiang L, Hu Y C,et al.Deployment of mobile robots with energy and timing constraints.IEEE Transactions on Robotics,2006,22(3):507-522
[144]史忠植.高级人工智能.北京：科学出版社,2006
[145]郑金华,陈振洲,蔡自兴.用遗传算法实现多智能体联盟的形成.计算机工程与科学,2004,26(6)：58-61
[146]夏娜,蒋建国,魏星,等.改进型蚁群算法求解单任务Agent联盟.计算机研究与发展, 2005,42(5):734-739
[147]Shehory O,Kraus S.Coalition formation among autonomous agents:strategy and complexity.In:Castelfranchi C Pmuller J Eds.From Reaction to Congnition, Lecture notes in Artificial Intelligence,Berlin:Springer,1993.57-72
[148]Ketchple S.Forming coalitions in the face of uncertain rewards.In Proceedings of AAAI-94, Seattle,USA,414-419
[149]Zoltkin G,Rosenschein J S.Coalition,cryptography, and stability:mechanisms for coalition formation in task oriented domains.In Proceedings of AAAI-94, Seattle,USA,432-437
[150]Sandholm T,Lesser V.Coaliton formation among computationally bounded agents. Artificial Intelligence,1997.94(1):88-137
[151]胡山立,石纯一.一种任一时间联盟结构生成算法.软件学报,2001,12(5)：729-734
[152]徐晋晖,张伟,石纯一.面向结构的Agent组织形成和演化机制.计算机研究与发展,2001,38(8)：897-903
[153]蒋建国,夏娜,齐美彬,等.一种基于蚁群算法的多任务联盟串行生成算法.电子学报,2005,33(12)：2178-2181
[154]张新良,石纯一.多Agent联盟结构动态生成算法.软件学报,2007,18(3)：574-581
[155]Shehory O,Kraus S.Methods for task allocation via agent coalition formation. Artificial Intelligence,1998.101:165-200
[156]Vig L, Adams J A. Coalition Formation:from software agents to robots. Journal of Intelligent and Robotic Systems,2007.50(1):85-118
[157]Sariel S, Balch T R,Erdogan N.Multiple traveling robot problem:a solution based on dynamic task selection and robust execution.IEEE/ASME Transactions on Mechatronics, 2009.14(2):198-206
[158]石纯一,张伟.基于Agent的计算.北京：清华大学出版社,2007
[159]傅祖芸.信息论——基础理论与应用.北京：电子工业出版社,2007
[160]Balch T.Hierarchic social entropy:an information theoretic measure of robot group diversity.Autonomous Robots,2000,8(3):209-237
[161]武志峰,黄厚宽.用差异演化算法求解单任务Agent联盟.计算机研究与发展,2006,43(增刊)：186-189
[162]张国富,蒋建国,夏娜,等.基于离散粒子群算法求解复杂联盟生成问题.电子学报2007,35(2)：323-327
[163]Kennedy J,Eberhart R C.A discrete binary version of the particle swarm algorithm.IEEE International conference on Systems,Masn and Cybernetics,1997
[164]Xu Xing,Li Yuanxiang,Wu Yu,et al.An analysis of the behavior of original discrete binary particle swarm optimization on trap functions.In Proceedings of 2008 International Conference on Computer Science and Software Engineering,2008.1207-1210.
[165]Clerc M, Kennedy J.The particle swarm:explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation,2002. 6(1):58-173
[166]HU Xiaohui, Eberhart R C. Adaptive particle swarm optimization:detection and response to dynamic systems.In Proceedings of the IEEE Congress on Evolutionary Computation, 2002.1666-1670
[167]Blackwell T M.Particle swarms and population diversity.Soft Computing,2005.9(11): 193-802
[168]Parrot D, LI Xiaodong.Locating and tracking multiple dynamic optima by a particle swarm model using speciation.IEEE Transactions on Evolutionary Computation,2006. 10(4):440-458
[169]高平安,蔡自兴.一种基于多子群的动态优化算法.中南大学学报(自然科学版)2009,40(3)：731-736
[170]Branke J.Memory enhanced evolutionary algorithms for changing optimization problems.In Proceedings of the 1999 Congress on Evolutionary Computation,1999. 3:1875-1882
[171]Blackwell T,Branke J.Multiswarms, exclusion, and anti-convergence in dynamic environments.IEEE Transactions on Evolutionary Computation,2006.10(4):459-472
[172]Zhang Yu,Liu Shuhua,Fu Shuai,et al.A quantum-inspired ant colony optimization for robot coalition formation.中国控制与决策会议(2009CCDC),桂林市,2009.626-631
[173]蔡自兴,肖正,于金霞.基于激光雷达的动态障碍物实时检测.控制工程,2008,15(2)：200-2003
[174]Feddema J,Lewis C,Schoenwald D.Decentralized control of cooperative robotic vehicles:theory and application.IEEE Transactions on Robotics and Automation,2002. 18(5):852-864
[175]desJardins M,Durfee E,Ortiz C,et.al.Survey of research in distributed, continual planning. AI Magazine,1999.20(4):13-22
[176]Dahl T S, Mataric M, Sukhatme G S.Multi-robot task allocation through vacancy chain scheduling.Robotics and Autonomous Systems,2009.57(6-7):674-687
[177]Kristina Lerman,Chris Jones,Aram Galstyan,et al.Analysis of dynamic task allocation in multi-robot systems.International Journal of Robotics research,2006.25(3):225-241
[178]Busquets D, Simmons R. Learning when to Auction and when to Bid. Distributed Autonomous Robotic Systems 7.Japan:Springer.2006.21-30
[179]Vigura A, Maza I, Ollero A. SET:an algorithm for distributed multirobot task allocation with dynamic negotiation based on task subsets. In Proceedings of 2007 IEEE International Conference on Robotics and Automation,Roma, Italy.2007.3339-3344
[180]Tovey C, Lagoudakis M, Jain S, Koenig S. The Generation of Bidding Rules for Auction-Based Robot Coordination. In Multi-Robot Systems:From Swarms to Intelligent Automata, L. Parker, F. Schneider and A. Schultz (eds), Springer.2005.3:3-14.
[181]Shim D,Kim H,Sastry S.Decentralized nonlinear model predictive control of multiple flying robots.In Proceedings of the IEEE Conference on Decision and Control,2003. 3621-3626
[182]Dongbing Gu,Huosheng Hu.A tabilizing receding horizon regular for nonholomic mobile robots.IEEE Transactions on Robotics,2005.21(5):1022-1028
[183]Leung C,Shoudong H,Kwoka N,et al.Planning under uncertainty using model predictive control for information gathering.Robotics and Autonomous Systems,2006.54(11): 898-910
[2]谭民,王硕,曹志强.多机器人系统.北京：清华大学出版社,2005
[3]美国国家航天局主页http://www.nasa.gov/topics/moonmars/index.html
[4]Saptharishi M,Spence O,Diehl C,et al.Distributed surveillance and reconnaissance using multiple autonomous ATVs:CyberScout.IEEE Transactions on Robotics and Automation. 2002,18(5):826-836
[5]Vidal R, Shakernia O,Kim H,et al.Probabilistic pursuit-evasion games:theory, implementation,and experimental evaluation.IEEE Transactions on Robotics and Automation.2002,18(5):662-669
[6]Trevai C, Ota Jun, Arai T.Multiple mobile robot surveillance in unknown environments. Advanced Robotics.2007,21 (7):729-749
[7]Stoeter S A, Rybski P E, Stubbs K N, et al.A robot team for surveillance tasks:Design and architecture.Robotics and Autonomous Systems.2002,40(2-3):173-183
[8]Fischer K,Miiller J P,Pischel M.Cooperative transportation scheduling:an application domain for DAI. Journal of Applied Artificial Intelligence,1995,9(10):1-33
[9]Nishi T, Ando M, Konishi M. Distributed route planning for multiple mobile robots using an augmented Lagrangian decomposition and coordination technique. IEEE Transactions on Robotics.2005,21(6):1191-1200
[10]Yongguo M,Yung-Hsiang L,Hu Y C,et al.Deployment of mobile robots with energy and timing constraints.IEEE Transactions on Robotics,2006,22(3):507-522
[11]Koes M,Nourbakhsh I,Sycara K.Constraint optimization coordination architecture for search and rescue robotics.In Proceedings of the IEEE International Conference on Robotics and Automation.Orlando,FL,USA. Piscataway,NJ,USA:IEEE.2006.3977-3982
[12]Burgard W, Moors M, Stachniss C, et al. Coordinated multi-robot exploration. IEEE Transactions on Robotics.2005,21(3):376-386
[13]李鹏,黄心汉,王敏.基于混合DSm模型的多机器人地图构建.计算机研究与发展,2009,46(1)：70-76
[14]王跃,谭民,景奉水,等.多机器人协调操作大型物体的运动学分析及应用.机器人,2002,24(5)：45 1-454
[15]周浦城,洪斌镕,蔡则苏.多机器人运动目标搜索策略研究.哈尔滨工业大学学报,2005,37(7)：879-882
[16]Fukuda T,Nakagawa S.A dynamically reconfigurable robotic system(concept of a system and optimal configurations).In Proceedings of International Conference on Industrial Electronics,Control,and Instrumentation,1987.588-595
[17]Asama H, Matsumoto A, Ishida Y.Design of an autonomous and distributed robot system: ACTRESS.In Proceedings of the IEEE/RSJ International Workshop on Intelligent Robots and Systems,1989.283-290
[18]Hackwood S, Beni G.Self-organization of sensors for swarm intelligence. In Proceedings of IEEE International Conference on Robotics and Automation,1992,819-829
[19]Parker L E.ALLIANCE:an architecture for fault tolerant multirobot cooperation.IEEE Transactions on Robotics and Automation.1998.14(2):220-240
[20]Alami R, Fleury S, Herrb M, et al. Multi-robot cooperation in the MARTHA project. IEEE Robotics & Automation Magazine,1998.36-47
[21]Dias M B.TraderBots:a new paradigm for robust and efficient multirobot coordination in dynamic environments [PhD Thesis].Carnegie Mellon University,2004
[22]苏丽颖,曹志强,王硕,等.多机器人对未知环境进行实时在线探测的一种方法.高技术通讯,2003,13(11)：56-60
[23]Jung B,Sukhatme G. Tracking targets using multiple robots:the effect of environment occlusion.Autonomous Robots,2002,13(3):191-205
[24]Simmons R,Singh S,Hershberger D,et al.First results in the coordination of heterogeneous robots for large-scale assembly.In Proceedings of the International Symposium on Experimental Robotics,Lecture Notes in Control and Information Sciences,2000.271:323-332
[25]王磊,唐华斌,孙增圻.多机器人系统形成联合协作的综合评价算法.清华大学学报(自然科学版).2005.45(4)：505-508
[26]Parker L E.Current research in multi-robot systems. Artificial Life Robotics,2003,7(1-2): 1-5
[27]范永,谭民MRCS中机器人控制体系框架结构.控制与决策,2000,15(3)：325-328
[28]孟宪松,刘建华,张铭钧.多水下机器人编队通信研究.中国造船,2007,48(4)：77-84
[29]陈卫东,席裕庚,顾冬雷,等.一个面向复杂任务的多机器人分布式协调系统.控制理论与应用,2002,19(4)：505-510
[30]刘传才,杨静宇,唐振民.多个自主机器人的协作策略研究.计算机学报,1998,21(10)：952-955
[31]吴智政,席裕庚.一种基于理性原则的多机器人协调控制.自动化学报,2000,26(4)：454-460
[32]蔡庆生,张波.一种基于Agent团队的强化学习模型与应用研究.计算机研究与发展,2000,37(9)：1087-1093
[33]顾国昌,仲宇,张汝波.一种新的多智能体强化学习算法及其在多机器人协作任务中的应用.机器人,2003,25(4)：344-349
[34]陈为雄,李振龙.基于BDI模型的多机器人智能体系统设计.机器人,2004,26(4)：310-313
[35]陈世明,方华京.大规模移动智能群体的建模及联合行为分析.控制与决策.2005,20(12)：1392-1396
[36]曾广周,杨公平,王晓琳.基于Agent能力自信度的任务分配问题研究.计算机学报,2007,30(11)：1922-1929
[37]丁滢颍,何衍,蒋静坪.基于蚁群算法的多机器人协作策略.机器人,2003,25(5)：414-418
[38]宋梅萍,顾国昌,张汝波.多移动机器人协作任务的分布式控制系统.机器人,2003,25(5)：456-460
[39]CAO Zhi-Qiang,ZHANG Bin,WANG Shuo,et al.Cooperative hunting of multiple mobile robots in an unknown environment自动化学报,2003,29(4)：536-543
[40]苏治宝,陆际联,童亮.一种多移动机器人协作围捕策略.北京理工大学学报,2004,24(5)：403-406
[41]Cao Y U, Fukunaga A S, Kahng A B, et al. Cooperative mobile robotics:antecedents and directions. Autonomous Robots,1997,4(1):1-23
[42]Farinelli A, Iocchi L, Nardi D. Multirobot systems:a classification focused on coordination. IEEE Transactions on Systems,Man,and Cybernetics, Part B:Cybernetics. 2004,34(5):2015-2128
[43]Parker L E.Distributed intelligence:overview of the field and its application in multi-robot systems. Journal of Physical Agents,2008,2(1):5-14
[44]Breed M D, Robinson G E, Page R E. Division of labor during honey bee colony defense. Behavioral Ecology and Sociobiology.1990,27(6):395-401
[45]Mataric M J. Designing emergent behaviors:from local interactions to collective intelligence. In:Meyer J A, Roitblat H, Wilson S (eds.).In Proceedings of the International Conference on Simulation of Adaptive Behavior:From Animals to Animats. USA:MIT Press.1992.(2):432-441
[46]Arkin R C.Cooperation without communication:multiagent schema-based robot navigation.Journal of robotic systems.1992,9(3):351-364
[47]Gordon D M.The organization of work in social insect colonies.Nature,1996,380: 121-124
[48]Krieger M, Billeter J B, Keller L.Ant-like task allocation and recruitment in cooperative robots.Nature.2000,406:992-996
[49]Labella T H, Dorigo M, Deneubourg J L.Division of Labor in a group of robots inspired by ants'foraging behavior.ACM Transactions on Autonomous and Adaptive Systems. 2006,1(1):4-25
[50]Chien S,Barrett A,Estlin T,et al.A comparison of coordinated planning methods for cooperating rovers.In Proceedings of the Fourth International Conference on Autonomous Agents,2000.100-101
[51]Gerkey B P, Mataric M J.et al.A framework for studying multi-robot task allocation. In Proceedings of Multi-Robot Systems:From Swarms to Intelligent Automata. Netherlands. Kluwer Academic Publishers.2003.2:15-26
[52]Howard A,Parker L E,Sukhatme G S.Experiments with a large heterogeneous mobile robot team:exploration,mapping,deployment and detection. International Journal of Robotics Research,2006,25(5-6):431-447
[53]Parker L E. Multiple mobile robot systems. Siciliano B, et al.(eds). Handbook of Robotics, Springer.2008.921-941
[54]Dias M B, Stentz A. A comparative study between centralized market-based and behavioral multi-robot coordination approaches. In Proceedings of the 2003 IEEE/RSJ International Conference Intelligent Robots and Systems, Las Vegas, Nevada.2003. 2279-2284
[55]Wooldridge M(英国).多Agent系统引论(石纯一,张伟,徐晋晖,等译).北京：电子工业出版社,2003,134-156
[56]堵丁柱,葛可一,王洁.计算复杂性导论.北京：高等教育出版社,2002.35-60
[57]Sandholm T. An implementation of the Contract Net Protocol based on marginal cost calculations. In Proceedings of the National Conference on Artificial Intelligence, Washington,D.C.1993.256-262
[58]Mataric M J. Issues and approaches in design of collective autonomous agents. Robotics and Autonomous Systems.1995.16(2-4):321-331
[59]Baghaei K, Agah A.Task allocation and communication methodologies for multi-robot systems.Intelligent Automation and Soft Computing,2003,9(4):217-226
[60]原魁,李园,房立新.多移动机器人系统研究发展近况.自动化学报.2007,33(8)：785-794
[61]Choudhury B B, Biswal B B. Task allocation methodologies for multi-robot systems. In Proceeding of the IEEE Sponsored Conference on Computational Intelligence, Control and Computer Vision in Robotics & Automation, NIT Rourkela.2008.99-106
[62]张嵛,刘淑华.多机器人任务分配的研究与进展.智能系统学报,2008,3(2)：1 15-120
[63]黎萍,杨宜民.多机器人系统任务分配的研究进展.计算机工程与应用,2008,44(17)：201-205
[64]Brumitt B L, Stentz A. Dynamic mission planning for multiple mobile robots. In Proceedings of IEEE International Conference on Robotics and Automation, Minneapolis, MN, USA.1996.(3):2396-2401
[65]Huntsberger T, Pirjanian P, Trebi-Ollennu A, et al. CAMPOUT:a control architecture for tightly coupled coordination of multirobot systems for planetary surface exploration. IEEE Transactions on Systems, Man, and Cybernetics-Part A:Systems and Humans.2003. 33(5):550-559
[66]Zhu A, Yang S X. A neural network approach to dynamic task assignment of multirobots. IEEE Transactions on Neural Network.2006.17(5):1278-1287
[67]黄宛宁,龚建伟,王鹏辉.基于改进遗传算法的多机器人任务分配方法.计算机仿真,2006,23(11)：164-168
[68]姜健,臧希喆,闫继宏,等.基于一种蚁群算法的多机器人动态感知任务分配.机器人,2008,30(3)：254-258
[69]余伶俐,蔡自兴.基于当代学习离散粒子群算法的多机器人任务分配.计算机应用研究,2009,26(5)：1691-1694
[70]Chaimowicz L, Campos M, Kumar V. Dynamic role assignment for cooperative robots. In Proceedings of 2002 IEEE International Conference on Robotics and Automation, Washington, DC, United states. USA:Institute of Electrical and Electronics Engineers Inc.2002.1:293-298
[71]Koes M,Nourbakhsh I,Sycara K.Constraint optimization coordination architecture for search and rescue robotics.In Proceedings of the IEEE International Conference on Robotics and Automation.Orlando,FL,USA. Piscataway,NJ,USA:IEEE.2006.3977-3982
[72]Koes M, Sycara K, Nourbakhsh I. A constraint optimization framework for fractured robot teams. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems.2006.491-493
[73]董胜龙,席裕庚,陈卫东.多机器人不确定协作任务的动态优化方法.机器人,2002,24(1)：31-34
[74]Gao Yunyuan, Wei Wei. Multi-robot autonomous cooperation integrated with immune based dynamic task allocation. In Proceedings of ISDA 2006:Sixth International Conference on Intelligent Systems Design and Applications. Jinan, China.2006.2: 586-591
[75]陈余庆,庄严,王伟.基于Petri网的多机器人协作任务分配与导航研究.大连理工大学学报,2008,48(4)：602-606
[76]Murhpy R,Lisetti C,Tardif R,et al.Emotion-based control of cooperating heterogeneous mobile robots.IEEE Transactions on Robotics and Automation,2002,18(5):744-757
[77]褚海涛,洪炳镕.nulti robots cooperative based on action selection level软件学报,2002,13(9)：1773-1778
[78]Simmons R, Apfelbaum D, Fox D, et al. Coordinated deployment of multiple heterogeneous robots. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS),2000.2254-2260
[79]Werger B, Mataric M J. Broadcast of local eligibility for multi-target observation. In: Parker L E, Bekey G, Barhen J (eds), Distributed autonomous Robotic Systems 4, New York:Springer-Verlag.2000.347-356
[80]姜健,闫继宏,臧希喆,等.基于信息素的多机器人协作任务分配.计算机工程与应用,2008,44(2)：20-22
[81]Dias M B, Zlot R, Kalra N, et al. Market-based multirobot coordination:a survey and analysis. In Proceedings of IEEE. Piscataway, NJ, USA:IEEE.2006.94(7):1257-1270
[82]张飞,陈卫东,席裕庚.多机器人协作探索的改进市场法.控制与决策,2005,20(5)：516-520
[83]Dias M. B, Stenz A. A free market architecture for distributed control of a multirobot system. In Proceedings of the 6th International Conference on Intelligent Autonomous Systems(IAS-6).2000.115-122
[84]Guerrero J, Oliver G. Physical interference impact in multi-robot task allocation auction methods. In Proceedings of the IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications, IEEE Computer Society,Washington, DC, USA.2006.19-24
[85]Scerri P, Farinelli A, Okamoto S. Allocating tasks in extreme teams. In Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, ACM New York,NY,USA.2005.727-734
[86]Botelho S C, Alami R. M+:A scheme for multi-robot cooperation through negotiated task allocation and achievement. In Proceedings of the 1999 IEEE International Conference on Robotics & Automation,Michigan,USA.1999.1234-1239
[87]Gerkey B P, Mataric M J. Sold!:auction methods for multi-robot coordination, IEEE Transactions on Robotics and Automation.2002.18(5):758-768
[88]Sariel S, Balch T, Erdogan N. Naval mine countermeasure missions. IEEE Robotics &
Automation Magazine.2008.15(1):45-52
[89]Zhou Pu-Cheng,Han Yu-Sheng,Xue Mo-Gen.Extended contract net protocol for multi-robot dynamic task allocation.Information Technology Journal,2007.6(5):733-738
[90]龙涛,沈林成,朱华勇,等.面向协同任务的多UCAV分布式任务分配与协调技术自动化学报,2007,33(7)：73 1-737
[91]Gong Jian-wei,Huang wan-ning,Xiong Guang-ming,et al. Genetic algorithm based combinatorial auction method for multi-robot task allocation.Journal of Beijing Institute of Technology,2007.16(2):151-156
[92]姜健,臧希喆,赵杰.基于焦虑概念和拍卖方法的多机器人协作搜集.控制与决策,2008,23(5)：541-545
[93]范永,谭民MRCS中机器人控制体系框架结构.控制与决策,2000,15(3)：325-328
[94]柳林,季秀才,郑志强.基于市场法及能力分类的多机器人任务分配方法.机器人,2006,28(3)：337-343
[95]Liu Lin, Zheng Zhiqiang. Combinatorial bids based multi-robot task allocation, In Proceedings of International Conference on Robotics and Automation, Barcelona,Spain, 2005.1145-1150
[96]Bertsekas D P. The auction algorithm for assignment and other network flow problem. Massachusetts Institute of Technology, Laboratory for Information and Decision Systems.1989.1908:15-17
[97]Chien S, Barrett A, Estlin T, et al. A comparison of coordinated planning methods for cooperating rovers.In Proceedings of the Fourth International Conference on Autonomous Agents, Barcelona, Spain.2000.100-101
[98]Cheng-Heng Fua,Shuzhi Sam Ge.COBOS:cooperative back off adaptive scheme for multi-robot task allocation.IEEE Transactions on Robotics.2005.21(6):1168-1178
[99]Zhang Dandan, Xie Guangming, Yu Junzhi, et al. Adaptive task assignment for multiple mobile robots via swarm intelligence approach. Robotics and Autonomous Systems, 2007,55(7):572-588
[100]王进戈,王强.基于模糊评判的机器人足球比赛策略研究.哈尔滨工业大学学报,2005,37(7)：943-946
[101]Gage A.Multi-robot task allocation using affect.[PhD Thesis],University of South Florida,2004
[102]Hanna H. Decentralized approach for multi-robot task allocation problem with uncertain task execution.In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2005),2005.535-540
[103]Tang F, Parker L E. A complete methodology for generating multi-robot task solutions using asymtred and market-based task allocation. In Proceedings of IEEE International Conference on Robotics and Automation (ICRA).2007.3351-3358
[104]Modi P J,Jung H,Tambe M,et al.Dynamic distributed resource allocation:a distributed constraint satisfaction approach.Lecture Notes in Computer Science,Intelligent Agents VIII,Springer Berlin,Heidelberg,2002,264-276
[105]Lagoudakis M G,Berhault M,Koenig S,et al.Simple auctions with performance guarantees for multi-robot task allocation.In Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).Piscataway, NJ,USA:IEEE.2004.1: 698-705
[106]Korte,Bernhard.Combinatorial optimization:theory and algorithms.Berlin, New York: Springer,2006
[107]刘任任,郑瑾.离散数学.长沙：中南大学出版社,2005
[108]Dudek G, Jenkin M, Milios E, et al. Taxonomy for multi-agent robotics.Autonomous Robots,1996.3(4):375-397
[109]Freedman P.Time,Petri Nets,and robotics.IEEE Transactions on Robotics and Automation, 1991.7(4):417-433
[110]Zlot R, Stentz A. Market-based multirobot coordination for complex tasks. International Journal of Robotics Research.2006.25(1):73-101
[111]Ghallab M(法),Nau D(美),Traverso P(意).自动规划-理论与实践(姜云飞,杨强,译).北京：清华大学出版社.2008
[112]Godwin M F,Spry S,Hedrick J K.Distributed collaboration with limited communication using mission state estimates. In Proceedings of 2006 American Control Conference. Piscataway,NJ,USA:IEEE.2006.14-16
[113]张铃,张钹.问题求解理论及应用-商空间粒度计算理论及应用(第2版).北京：清华大学出版社,2007
[114]Kara I, Bektas T. Integer linear programming formulations of multiple salesman problems and its variations. European Journal of Operational Research,2006.174(3): 1449-1458
[115]Pagello E, D'Angelo A, Menegatti E. Cooperation issues and distributed sensing for multirobot systems.In Proceedings of the IEEE. USA:Institute of Electrical and Electronics Engineers Inc.2006.94(7):1370-1383
[116]Pongpunwattana A,Rysdyk R.Real-time planning for multiple autonomous vehicles in dynamic uncertain environments.Journal of Aerospace Computing, Information,and
Communication,2004.1(12):580-604
[117]Vig L,Adams J A.Multi-robot coalition formation.IEEE Transactions on Robotics.2006. 22(4):637-649
[118]Kagel J H,Levin D共同价值拍卖与赢者灾难.董保民,王勇等译.北京：中国人民大学出版社,2007
[119]Smith R G. The contract net protocol:high-level communication and control in a distributed Problem Solver. IEEE Transactions on.Computers.1980. C-29(12): 1104-1113
[120]Sandholm T. Contract types for satisficing task allocation:Ⅰ theoretical results. AAAI 1998 Spring Symposium:Satisficing Models, Stanford University, California.1998.68-75
[121]Sandholm T S, Lesser V R. Advantages of a leveled commitment contracting protocol. Technical Report:UM-CS-1995-072, University of Massachusetts Amherst,MA,USA. 1995
[122]Excelente-Toledo C, Bourne R, Jennings N. Reasoning about commitments and penalties for coordination between autonomous agents. In Proceedings of the fifth international conference on Autonomous agents, Montreal, Quebec, Canada.2001.131-138
[123]Aknine S, Pinson S, Shakun M F. An extended multi-agent negotiation protocol. Autonomous Agents and Multi-Agent Systems,2004.8(1):5-45
[124]Xu Y, Scerri P, Sycara K, Lewis M. Comparing market and token-based coordination. In Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems. Hakodate, Japan.2006.1113-1115
[125]Knabe T,Schillo M,Fischer K.Improvements to the FIPA Contract Net Protocol for performance increase and cascading applications.In International Workshop for Multi-Agent Interoperability at the German Conference on AI,2002,http://citeseerx.ist. psu.edu/viewdoc/summary?doi= 10.1.1.19.9772
[126]宋海刚,陈学广.合同网协议中的Agent可用度研究.计算机科学,2004,31(8)：127-129
[127]万武南,王晓京,宋春雨等.基于范例推理的合同网模型.小型微型计算机系统,2005,26(9)：1578-1581
[128]Deshpande U, Gupta A, Basu A. Performance enhancement of a contract net protocol based system through instance-based learning. IEEE Transactions on Systems, Man, and Cybernetics-part B:Cybernetics.2005.35(2):345-358
[129]Parker L E. Lifelong adaptation in heterogeneous multi-robot teams:response to continual variation in individual robot performance. Autonomous Robots,2000.8(3): 239-267
[130]Sandholm T,Suri S.BOB:Improved winner determination in combinatorial auctions and generalizations.Artificial Intelligence,2003,145:33-58
[131]Lagoudakis M, Markakis V, Kempe D, et al.Auction-Based Multi-Robot Routing.In Proceedings of the International Conference on Robotics:Science and Systems,2005. 343-350
[132]Koenig S, Tovey C, Lagoudakis M, et al. The power of sequential single-item auction for agent coordination. In Proceedings of the Twenty-First National Conference on Artificial Intelligence(AAAI-06).Boston,MA,USA.2007.2:1625-1629
[133]Andersson M, Sandholm T.Time-quality tradeoffs in reallocative negotiation with combinatorial contract types. In Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference.Orlando, Florida, USA.1999.3-10
[134]Berhault M, Huang H, Keskinocal P, et al. Robot exploration with combinatorial auctions. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.2003.2:1957-1962
[135]Surmann H,Morales A.Scheduling tasks to a team of autonomous mobile service robots in indoor environments.Journal of universal computer science,2002,8(8):809-833
[136]王树禾.图论.北京：科学出版社,2004
[137]Leung Yiu-Wing,Yuping Wang.An orthogonal genetic algorithm with quantization for global numerical optimization.IEEE Transactions on Evolutionary Computation,2001, 5(1):41-53
[138]史奎凡,董吉文,李金屏,等.正交遗传算法.电子学报,2002,30(10)：1501-1504
[139]杨子胥.正交表的构造.济南：山东人民出版社,1978.110-181
[140]http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsplib.html
[141]Ralphs T.Vehicle Routing Data Sets.http://www.coin-or.org/SYMPHONY/branchandcut/ VRP/data/#A, maintained by Ted Ralphs,2008
[142]高平安,蔡自兴.多移动机器人任务负载均衡分组规划算法法.高技术通讯,2009,19(5)：501-505
[143]Yongguo M, Yung-Hsiang L, Hu Y C,et al.Deployment of mobile robots with energy and timing constraints.IEEE Transactions on Robotics,2006,22(3):507-522
[144]史忠植.高级人工智能.北京：科学出版社,2006
[145]郑金华,陈振洲,蔡自兴.用遗传算法实现多智能体联盟的形成.计算机工程与科学,2004,26(6)：58-61
[146]夏娜,蒋建国,魏星,等.改进型蚁群算法求解单任务Agent联盟.计算机研究与发展, 2005,42(5):734-739
[147]Shehory O,Kraus S.Coalition formation among autonomous agents:strategy and complexity.In:Castelfranchi C Pmuller J Eds.From Reaction to Congnition, Lecture notes in Artificial Intelligence,Berlin:Springer,1993.57-72
[148]Ketchple S.Forming coalitions in the face of uncertain rewards.In Proceedings of AAAI-94, Seattle,USA,414-419
[149]Zoltkin G,Rosenschein J S.Coalition,cryptography, and stability:mechanisms for coalition formation in task oriented domains.In Proceedings of AAAI-94, Seattle,USA,432-437
[150]Sandholm T,Lesser V.Coaliton formation among computationally bounded agents. Artificial Intelligence,1997.94(1):88-137
[151]胡山立,石纯一.一种任一时间联盟结构生成算法.软件学报,2001,12(5)：729-734
[152]徐晋晖,张伟,石纯一.面向结构的Agent组织形成和演化机制.计算机研究与发展,2001,38(8)：897-903
[153]蒋建国,夏娜,齐美彬,等.一种基于蚁群算法的多任务联盟串行生成算法.电子学报,2005,33(12)：2178-2181
[154]张新良,石纯一.多Agent联盟结构动态生成算法.软件学报,2007,18(3)：574-581
[155]Shehory O,Kraus S.Methods for task allocation via agent coalition formation. Artificial Intelligence,1998.101:165-200
[156]Vig L, Adams J A. Coalition Formation:from software agents to robots. Journal of Intelligent and Robotic Systems,2007.50(1):85-118
[157]Sariel S, Balch T R,Erdogan N.Multiple traveling robot problem:a solution based on dynamic task selection and robust execution.IEEE/ASME Transactions on Mechatronics, 2009.14(2):198-206
[158]石纯一,张伟.基于Agent的计算.北京：清华大学出版社,2007
[159]傅祖芸.信息论——基础理论与应用.北京：电子工业出版社,2007
[160]Balch T.Hierarchic social entropy:an information theoretic measure of robot group diversity.Autonomous Robots,2000,8(3):209-237
[161]武志峰,黄厚宽.用差异演化算法求解单任务Agent联盟.计算机研究与发展,2006,43(增刊)：186-189
[162]张国富,蒋建国,夏娜,等.基于离散粒子群算法求解复杂联盟生成问题.电子学报2007,35(2)：323-327
[163]Kennedy J,Eberhart R C.A discrete binary version of the particle swarm algorithm.IEEE International conference on Systems,Masn and Cybernetics,1997
[164]Xu Xing,Li Yuanxiang,Wu Yu,et al.An analysis of the behavior of original discrete binary particle swarm optimization on trap functions.In Proceedings of 2008 International Conference on Computer Science and Software Engineering,2008.1207-1210.
[165]Clerc M, Kennedy J.The particle swarm:explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation,2002. 6(1):58-173
[166]HU Xiaohui, Eberhart R C. Adaptive particle swarm optimization:detection and response to dynamic systems.In Proceedings of the IEEE Congress on Evolutionary Computation, 2002.1666-1670
[167]Blackwell T M.Particle swarms and population diversity.Soft Computing,2005.9(11): 193-802
[168]Parrot D, LI Xiaodong.Locating and tracking multiple dynamic optima by a particle swarm model using speciation.IEEE Transactions on Evolutionary Computation,2006. 10(4):440-458
[169]高平安,蔡自兴.一种基于多子群的动态优化算法.中南大学学报(自然科学版)2009,40(3)：731-736
[170]Branke J.Memory enhanced evolutionary algorithms for changing optimization problems.In Proceedings of the 1999 Congress on Evolutionary Computation,1999. 3:1875-1882
[171]Blackwell T,Branke J.Multiswarms, exclusion, and anti-convergence in dynamic environments.IEEE Transactions on Evolutionary Computation,2006.10(4):459-472
[172]Zhang Yu,Liu Shuhua,Fu Shuai,et al.A quantum-inspired ant colony optimization for robot coalition formation.中国控制与决策会议(2009CCDC),桂林市,2009.626-631
[173]蔡自兴,肖正,于金霞.基于激光雷达的动态障碍物实时检测.控制工程,2008,15(2)：200-2003
[174]Feddema J,Lewis C,Schoenwald D.Decentralized control of cooperative robotic vehicles:theory and application.IEEE Transactions on Robotics and Automation,2002. 18(5):852-864
[175]desJardins M,Durfee E,Ortiz C,et.al.Survey of research in distributed, continual planning. AI Magazine,1999.20(4):13-22
[176]Dahl T S, Mataric M, Sukhatme G S.Multi-robot task allocation through vacancy chain scheduling.Robotics and Autonomous Systems,2009.57(6-7):674-687
[177]Kristina Lerman,Chris Jones,Aram Galstyan,et al.Analysis of dynamic task allocation in multi-robot systems.International Journal of Robotics research,2006.25(3):225-241
[178]Busquets D, Simmons R. Learning when to Auction and when to Bid. Distributed Autonomous Robotic Systems 7.Japan:Springer.2006.21-30
[179]Vigura A, Maza I, Ollero A. SET:an algorithm for distributed multirobot task allocation with dynamic negotiation based on task subsets. In Proceedings of 2007 IEEE International Conference on Robotics and Automation,Roma, Italy.2007.3339-3344
[180]Tovey C, Lagoudakis M, Jain S, Koenig S. The Generation of Bidding Rules for Auction-Based Robot Coordination. In Multi-Robot Systems:From Swarms to Intelligent Automata, L. Parker, F. Schneider and A. Schultz (eds), Springer.2005.3:3-14.
[181]Shim D,Kim H,Sastry S.Decentralized nonlinear model predictive control of multiple flying robots.In Proceedings of the IEEE Conference on Decision and Control,2003. 3621-3626
[182]Dongbing Gu,Huosheng Hu.A tabilizing receding horizon regular for nonholomic mobile robots.IEEE Transactions on Robotics,2005.21(5):1022-1028
[183]Leung C,Shoudong H,Kwoka N,et al.Planning under uncertainty using model predictive control for information gathering.Robotics and Autonomous Systems,2006.54(11): 898-910