群机器人系统自组织队形控制策略研究

发布时间：2018-08-24 08:32

【摘要】：随着科学技术的不断发展,人工智能已经成为当今世界的热点问题,其中的群机器人技术也得到了众多专家和学者的广泛关注。群机器人系统具有高度的灵活性、较好的鲁棒性,并且系统中的单智能体行为相对简单、复杂度低。基于此,群机器人系统在各个领域都得到了广泛的应用,成为当今世界的研究热点。本文针对群机器人系统队形控制问题,提出了一种基于安全区域的群机器人自组织队形控制策略,并使用e-Puck机器人在其仿真器Webots中完成了相应的队形控制任务。首先,本文对群机器人系统的研究背景和意义进行充分说明,并对国内外群机器人系统研究现状做出概述,对群机器人研究中的热点问题进行简述,对群机器人研究中相关智能优化算法进行简要分析。在充分了解了群机器人系统的国内外研究背景和相关研究方法的基础上,分析了群机器人系统的系统特性,深入了解了其协同合作方法。进而通过对群机器人系统特性的分析,选取e-Puck为本文的实验用机器人,并针对由以e-Puck为例的轮式移动机器人组成的群机器人系统中的个体机器人进行了运动学分析,构造了群机器人系统中个体机器人的运动行为模型,给出了机器人速度大小和方向的控制方法。其次,本文通过对人工势场法的思路分析引出安全区域的概念,给出群机器人系统中个体机器人的运动规划图,根据已建立的个体机器人运动行为模型构造出群机器人自组织队形控制的势场函数,建立安全区域,并根据安全区域进行建模,使得机器人在从初始位置向目标点运动的过程中,满足在远离目标点时,机器人之间的互联制约影响小,使之集中;而在靠近目标点时互联制约影响大,使之分散。从而使群机器人协调成相互之间趋于分散且群体集中于目标点的队形。在此规则的基础上,给出边界方程等限制条件,使得群机器人系统中各机器人可根据个体之间及个体与环境之间的局部交互自组织完成指定队形任务。最后,本文给出了机器人到达指定目标点、机器人完成聚集、机器人组成圆形、机器人组成L形四种群机器人队形控制任务的具体算法步骤和相应流程图。进而选取e-Puck为实验机器人,Webots为其仿真器,通过一系列仿真实验,对文中提出的方法进行了验证,并对实验结果进行了总结和分析。最终实验结果表明了本文提出的针对以e-Puck机器人为例的群机器人系统基于安全区域的自组织队形控制策略,在完成队形控制任务上具有可行性和有效性。
[Abstract]:With the continuous development of science and technology, artificial intelligence has become a hot issue in the world, and the swarm robot technology has been widely concerned by many experts and scholars. The swarm robot system has high flexibility, good robustness, and the behavior of single agent in the system is relatively simple and the complexity is low. Based on this, swarm robot system has been widely used in various fields, and has become a research hotspot in the world. In order to solve the problem of formation control of swarm robot system, this paper presents a self-organizing formation control strategy for swarm robot based on secure region, and uses e-Puck robot to complete the corresponding formation control task in its simulator Webots. First of all, the research background and significance of the swarm robot system are explained in this paper, and the current research situation of the swarm robot system at home and abroad is summarized, and the hot issues in the research of the swarm robot system are briefly described. The related intelligent optimization algorithms in the research of swarm robots are briefly analyzed. On the basis of fully understanding the domestic and international research background and related research methods of swarm robot system, the characteristics of swarm robot system are analyzed, and the cooperative cooperation method is deeply understood. Then, through the analysis of the characteristics of the swarm robot system, e-Puck is selected as the experimental robot in this paper, and the kinematics of the individual robot in the group robot system composed of the wheeled mobile robot with e-Puck as an example is analyzed. The motion behavior model of individual robot in swarm robot system is constructed, and the control method of robot speed and direction is given. Secondly, by analyzing the method of artificial potential field, the concept of safe area is introduced, and the movement plan of individual robot in swarm robot system is given. According to the established individual robot motion behavior model, the potential field function of self-organized formation control of swarm robots is constructed, and the safety area is established, and the model is built according to the safety region. In the process of moving from the initial position to the target point, the robot is satisfied that the interlinkage restriction between the robots has little influence and makes the robot concentrate when it is far away from the target point, but when the robot is near the target point, the influence of the interconnected constraint is great, which makes the robot disperse. Thus, the swarm robots are coordinated into a formation where each group tends to be dispersed and the group concentrates on the target point. On the basis of this rule, the boundary equation and other limiting conditions are given, so that each robot in a swarm robot system can self-organize to complete the task of assigned formation according to the local interaction between individuals and environment. Finally, this paper presents the algorithm and flow chart of the formation control task of the robot to reach the designated target point, the robot to complete the aggregation, the robot to form a circle, and the robot to form the L-shaped four-species robot formation control task. Then e-Puck is chosen as the simulator of the experimental robot, and the proposed method is verified by a series of simulation experiments, and the experimental results are summarized and analyzed. Finally, the experimental results show that the self-organizing formation control strategy based on safe region for the e-Puck robot system proposed in this paper is feasible and effective in completing the formation control task.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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