群体机器人系统合作控制问题研究
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摘要
近年来,随着多机器人系统规模的不断增大,系统控制复杂度及机器人之间的通信量成指数倍地增加,难以利用传统的方法解决。而自然界中广泛存在的蚁群、鸟群和鱼群等社会生物群体所涌现出的群体智能(Swarm Intelligence),给多机器人研究提供了很好的启发,于是产生了一个新的研究领域——群体机器人学(Swarm Robotics)。与结构越来越复杂的单个机器人和传统的多机器人系统相比,群体机器人系统的鲁棒性、可扩展性、灵活性和经济性都占有更大优势,具有广泛的应用前景。本论文针对群体机器人系统合作控制中的一些关键理论、技术和典型任务进行了深入的研究,提出了一些新的方法。本文的主要内容有：
1.合作控制中的一致性理论和方法。合作控制中的一个关键问题就是设计合适的一致性方法和策略,使群体间共享的信息形成一致性。针对这个问题,本文基于代数图论提出了表征群体机器人个体之间信息交互关系和状态的“信息交互图”和“信息交互矩阵”等概念,并利用矩阵论和控制论等理论知识,证明了群体系统形成一致的充要条件。在此基础上,研究了群体机器人一阶系统和二阶系统在固定交互拓扑和动态交互拓扑情况下的一致性策略和方法,并针对存在误差、扰动、延时以及输入受限等情况下的一致性方法做出了相应的分析,同时结合仿真实例对所提一致性方法做出了验证。
2.群体机器人的编队控制问题。编队控制是群体机器人合作控制问题中的一个典型任务。本文在"boids"模型的基础上利用一致性理论分析了一阶系统“boids”模型的一致性方法；同时,通过构建虚拟势场力以及相应的一致性策略,提出了一种二阶系统的群体机器人编队控制方法,并根据代数图论和LaSalle不变性原理证明了其稳定性。在此基础上,利用行为融合的方法提出了一种有障碍物环境中的群集编队控制方法。
3.群体机器人的目标搜索问题。目标搜索是在指一群机器人在一个给定的环境中通过合作寻找一个未知的目标点,这也是一个典型的合作控制问题。本文分别从群体机器人的通信拓扑关系,以及实际的搜寻策略与方法两个方面对目标搜索问题进行阐述。介绍了一种基于粒子群优化(PSO)的搜索方法来控制一群机器人在未知环境中搜索目标,和标准PSO算法比较,该方法考虑了机器人的实际运动特性和工作环境约束。同时,针对群体机器人目标搜索中的通信拓扑关系,利用一致性理论进行了阐述,给出了目标搜索任务能够完成的条件。
4.群体机器人的可控问题。群体机器人系统存在着一个显著的问题：即控制结果往往不可控,很难达到一个期望的状态。本文把这个问题称之为群体机器人系统的“可控问题”：即如何在不改变机器人个体现有一致性规则的情况下,控制群体机器人达到一个期望的状态。针对这个问题,本文分别介绍了两种一阶系统的一致性跟踪方法,以使群体机器人的状态与一个时不变或是时变的参考状态渐进形成一致。在此基础上,结合无线传感器网络和群体机器人系统的特点,介绍了一种基于无线传感器网络的“虚形体”技术。利用在传感器网络节点上构造具有群体系统其他实体特征的虚形体,通过虚形体干预机器人实体的运动状态,使实体机器人群体运动有序可控,实现群体机器人系统的合作控制。
As the scale of multi-robot systems is increasing in recent years, the system control complexity and the communication traffic of multiple robots will exponentially increase, and it is difficult to use traditional algorithms to solve this problem. In nature, there are many social insects---ants, termites, wasps and bees—which can be standed as fascinating examples of how collectively intelligent systems can be generated from a large number of simple individuals. Biologists, computer scientists and roboticists teamed up to transfer their knowledge of social insects behavior to the design of controllers for multi-robot systems. This combined, multidisciplinary effort gave birth to the field of research known as swarm robotics.
Campared with the complex single robot and the tranditional multi-robot systems, the characteristics of swarm robotics, such as robustness, scalability, flexiblility and low cost, are better than them. So it will be well researched and widely used in the future. In this thesis, we focused on the cooperative control problem of swarm robotics, and presented some new theories, techniques and algorithms, as follows:
1. For consensus problem, we defined the information interactive graph and the information interactive matrix to represent the information interaction relationship and state between each robot based on algebra graph theroy. Proofed the necessary and/or sufficient conditions for consensus and presented some consensus algorithms under static and dynamic topology with error, disturbance, time delay, and input constrains for the first order and the second order sytem, respectively.
2. For formation control problem, we analysed the "boids" model using the consensus algorithm for the first order system, and presented two formation control algorithms for the second order system using the virtual force and the flocking theory. Based on the behavior fusion algorithm and the above works, we introduced a flocking formation control algorithm with obstacle avoidance.
3. For target searching problem, we introduced a new searching algorithm based on the particle swarm optimization in the enviornment with obstacles. And analysed the influence of information topology of a group of robots for searching task.
4. For swarm controllable problem, we introduced two consensus state tracking algorithms. And invented the "Virtual Entity" technique to sovle the controllable problem for a group of robots based on the wireless sensor network.
1.合作控制中的一致性理论和方法。合作控制中的一个关键问题就是设计合适的一致性方法和策略,使群体间共享的信息形成一致性。针对这个问题,本文基于代数图论提出了表征群体机器人个体之间信息交互关系和状态的“信息交互图”和“信息交互矩阵”等概念,并利用矩阵论和控制论等理论知识,证明了群体系统形成一致的充要条件。在此基础上,研究了群体机器人一阶系统和二阶系统在固定交互拓扑和动态交互拓扑情况下的一致性策略和方法,并针对存在误差、扰动、延时以及输入受限等情况下的一致性方法做出了相应的分析,同时结合仿真实例对所提一致性方法做出了验证。
2.群体机器人的编队控制问题。编队控制是群体机器人合作控制问题中的一个典型任务。本文在"boids"模型的基础上利用一致性理论分析了一阶系统“boids”模型的一致性方法；同时,通过构建虚拟势场力以及相应的一致性策略,提出了一种二阶系统的群体机器人编队控制方法,并根据代数图论和LaSalle不变性原理证明了其稳定性。在此基础上,利用行为融合的方法提出了一种有障碍物环境中的群集编队控制方法。
3.群体机器人的目标搜索问题。目标搜索是在指一群机器人在一个给定的环境中通过合作寻找一个未知的目标点,这也是一个典型的合作控制问题。本文分别从群体机器人的通信拓扑关系,以及实际的搜寻策略与方法两个方面对目标搜索问题进行阐述。介绍了一种基于粒子群优化(PSO)的搜索方法来控制一群机器人在未知环境中搜索目标,和标准PSO算法比较,该方法考虑了机器人的实际运动特性和工作环境约束。同时,针对群体机器人目标搜索中的通信拓扑关系,利用一致性理论进行了阐述,给出了目标搜索任务能够完成的条件。
4.群体机器人的可控问题。群体机器人系统存在着一个显著的问题：即控制结果往往不可控,很难达到一个期望的状态。本文把这个问题称之为群体机器人系统的“可控问题”：即如何在不改变机器人个体现有一致性规则的情况下,控制群体机器人达到一个期望的状态。针对这个问题,本文分别介绍了两种一阶系统的一致性跟踪方法,以使群体机器人的状态与一个时不变或是时变的参考状态渐进形成一致。在此基础上,结合无线传感器网络和群体机器人系统的特点,介绍了一种基于无线传感器网络的“虚形体”技术。利用在传感器网络节点上构造具有群体系统其他实体特征的虚形体,通过虚形体干预机器人实体的运动状态,使实体机器人群体运动有序可控,实现群体机器人系统的合作控制。
As the scale of multi-robot systems is increasing in recent years, the system control complexity and the communication traffic of multiple robots will exponentially increase, and it is difficult to use traditional algorithms to solve this problem. In nature, there are many social insects---ants, termites, wasps and bees—which can be standed as fascinating examples of how collectively intelligent systems can be generated from a large number of simple individuals. Biologists, computer scientists and roboticists teamed up to transfer their knowledge of social insects behavior to the design of controllers for multi-robot systems. This combined, multidisciplinary effort gave birth to the field of research known as swarm robotics.
Campared with the complex single robot and the tranditional multi-robot systems, the characteristics of swarm robotics, such as robustness, scalability, flexiblility and low cost, are better than them. So it will be well researched and widely used in the future. In this thesis, we focused on the cooperative control problem of swarm robotics, and presented some new theories, techniques and algorithms, as follows:
1. For consensus problem, we defined the information interactive graph and the information interactive matrix to represent the information interaction relationship and state between each robot based on algebra graph theroy. Proofed the necessary and/or sufficient conditions for consensus and presented some consensus algorithms under static and dynamic topology with error, disturbance, time delay, and input constrains for the first order and the second order sytem, respectively.
2. For formation control problem, we analysed the "boids" model using the consensus algorithm for the first order system, and presented two formation control algorithms for the second order system using the virtual force and the flocking theory. Based on the behavior fusion algorithm and the above works, we introduced a flocking formation control algorithm with obstacle avoidance.
3. For target searching problem, we introduced a new searching algorithm based on the particle swarm optimization in the enviornment with obstacles. And analysed the influence of information topology of a group of robots for searching task.
4. For swarm controllable problem, we introduced two consensus state tracking algorithms. And invented the "Virtual Entity" technique to sovle the controllable problem for a group of robots based on the wireless sensor network.
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