基于改进人工势场法的足球机器人路径规划研究
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摘要
足球机器人是机器人研究领域的重要课题,近年来得到迅速的发展,目前国际上组织并开展了多种机器人足球比赛。其中,RoboCup中型组机器人足球比赛就是一项比较著名的比赛。比赛环境的复杂性和随机性,使得路径规划问题成为足球机器人研究领域的一个重点。它涉及到感知、定位、通信、分布控制等技术,是一个多融合的综合性课题。
本文以Robocup中型组足球机器人比赛为研究背景。首先介绍了国内外足球机器人和路径规划的研究现状和发展,RoboCup中型组足球机器人比赛及足球机器人系统的构成和软件环境。作为对路径规划深入研究的基础,介绍了所采用的环境建模方法和障碍物检测方法,并对路径规划算法进行分类、综合分析其各自的特点。其次,在对足球机器人系统全面分析的基础上,重点研究机器人系统中路径规划问题。通过分析对比各种方法优缺点,选择人工势场法进行深入研究,并针对其存在的不足提出改进方法以提高路径规划的效果。由于人工势场法是局部路径规划方法,存在局部极小值问题。针对其在复杂的比赛环境中不能满足足球机器人路径规划对实时性、安全性和可达性的要求,通过修改势场力函数和势场力方向避免路径规划的失败。考虑到比赛场上的竞争性和足球机器人的运动性,引入了受速度影响势场力分量,并设计了调节势场力大小的模糊控制器,提出动态模糊人工势场法。在此基础上,为了更好的搜索最优路径,引入遗传算法,进化路径,形成动态模糊进化人工势场法。最后在MATLAB平台下应用此方法进行仿真实验,针对不同区域下典型位置和运动状态下的路径规划进行细致的分析。改进后的方法克服了传统人工势场法的局部极小值问题,同时提高了规划的精度和实时性。仿真实验验证了方法的有效性。
Soccer Robot is an important subject area of robotics research.In recent years,it has been developing rapidly, and many kinds of Soccer Robot international competitions are organized,among which RoboCup medium-sized group robot soccer is a more well-known gameThe complexity and randomness of environment in robot soccer game make path planning be a priority research on soccer robot,which technology level decide the quality of the game. It refers to the perception, positioning, communications, distributed control technology, is a multi-subject integrated and comprehensive.
In this paper, medium-sized group of Robocup robot soccer competition is research background. Firstly, introduced the domestic and international soccer robot and path planning Research and development, mid-sized group of RoboCup robot soccer competition and the composition and software environment of the soccer robot system. As the basis for Path planning in-depth study, a description of the methods used in environmental modeling and obstacle detection methods has been introduced, and classified path planning algorithms, comprehensively analysed their respective characteristics. Secondly, based on a comprehensive analysis of the soccer robot system, the key research on path planning problems is carried on .By analyzing and Comparing the advantages and disadvantages of various methods, chose the artificial potential field method as in-depth study and proposed improved method for overcoming its shortcomings to improve the path planning results. As the artificial potential field method is a local path planning method, there is local minimum problem, and can not satisfy requirements of soccer robot path planning for real-time, safety and accessibility in dynamic environment. For the problems of traditional artificial potential field method in a complex game environment, modified the potential field force function and potential field force direction to avoid the failure of path planning. Taking into account the competitive playing field and the movement of agent, this paper introduced the velocity as the impact of factors into potential field force function, designed the fuzzy controller to regulate the size of artificial potential field force, and proposed dynamic fuzzy artificial potential field method. On this basis, in order to better search the optimal path, introduced genetic algorithms for evolving path, and proposed the dynamic fuzzy evolutionary potential field method. Finally, an simulation experiment was carried on by the method on the MATLAB platform. Analyzed path planning according different regions and state of different location and movement. The improved method can overcome the traditional artificial potential field method of the local minimum problem, while improving planning accuracy and real-time. Simulated experiment certificated the effectiveness of the method.
本文以Robocup中型组足球机器人比赛为研究背景。首先介绍了国内外足球机器人和路径规划的研究现状和发展,RoboCup中型组足球机器人比赛及足球机器人系统的构成和软件环境。作为对路径规划深入研究的基础,介绍了所采用的环境建模方法和障碍物检测方法,并对路径规划算法进行分类、综合分析其各自的特点。其次,在对足球机器人系统全面分析的基础上,重点研究机器人系统中路径规划问题。通过分析对比各种方法优缺点,选择人工势场法进行深入研究,并针对其存在的不足提出改进方法以提高路径规划的效果。由于人工势场法是局部路径规划方法,存在局部极小值问题。针对其在复杂的比赛环境中不能满足足球机器人路径规划对实时性、安全性和可达性的要求,通过修改势场力函数和势场力方向避免路径规划的失败。考虑到比赛场上的竞争性和足球机器人的运动性,引入了受速度影响势场力分量,并设计了调节势场力大小的模糊控制器,提出动态模糊人工势场法。在此基础上,为了更好的搜索最优路径,引入遗传算法,进化路径,形成动态模糊进化人工势场法。最后在MATLAB平台下应用此方法进行仿真实验,针对不同区域下典型位置和运动状态下的路径规划进行细致的分析。改进后的方法克服了传统人工势场法的局部极小值问题,同时提高了规划的精度和实时性。仿真实验验证了方法的有效性。
Soccer Robot is an important subject area of robotics research.In recent years,it has been developing rapidly, and many kinds of Soccer Robot international competitions are organized,among which RoboCup medium-sized group robot soccer is a more well-known gameThe complexity and randomness of environment in robot soccer game make path planning be a priority research on soccer robot,which technology level decide the quality of the game. It refers to the perception, positioning, communications, distributed control technology, is a multi-subject integrated and comprehensive.
In this paper, medium-sized group of Robocup robot soccer competition is research background. Firstly, introduced the domestic and international soccer robot and path planning Research and development, mid-sized group of RoboCup robot soccer competition and the composition and software environment of the soccer robot system. As the basis for Path planning in-depth study, a description of the methods used in environmental modeling and obstacle detection methods has been introduced, and classified path planning algorithms, comprehensively analysed their respective characteristics. Secondly, based on a comprehensive analysis of the soccer robot system, the key research on path planning problems is carried on .By analyzing and Comparing the advantages and disadvantages of various methods, chose the artificial potential field method as in-depth study and proposed improved method for overcoming its shortcomings to improve the path planning results. As the artificial potential field method is a local path planning method, there is local minimum problem, and can not satisfy requirements of soccer robot path planning for real-time, safety and accessibility in dynamic environment. For the problems of traditional artificial potential field method in a complex game environment, modified the potential field force function and potential field force direction to avoid the failure of path planning. Taking into account the competitive playing field and the movement of agent, this paper introduced the velocity as the impact of factors into potential field force function, designed the fuzzy controller to regulate the size of artificial potential field force, and proposed dynamic fuzzy artificial potential field method. On this basis, in order to better search the optimal path, introduced genetic algorithms for evolving path, and proposed the dynamic fuzzy evolutionary potential field method. Finally, an simulation experiment was carried on by the method on the MATLAB platform. Analyzed path planning according different regions and state of different location and movement. The improved method can overcome the traditional artificial potential field method of the local minimum problem, while improving planning accuracy and real-time. Simulated experiment certificated the effectiveness of the method.
引文
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[7]段俊花,李孝安,刘立云.人工势场法在足球机器人路径规划中的应用[J].计算机仿真, 2008,25(12): 192-195
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[10]张祺.基于视觉的机器人足球比赛系统研究[D],广东:广东工业大学,2003
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[13]张亚鸣,雷小宇,杨胜跃,樊晓平,瞿志华,贾占朝.多机器人路径规划研究方法[J].计算机应用与研究,2008,25(9):2567~2569.
[14]何利.微型足球机器人路径规划研究[D],天津:天津大学,2005
[15] Vandi Verma, Reid G.Simmons. Scalable robot fault detectiong and identification. Robotics and Autonomous Systems 54(2):184~191
[16]金勇.基于进化势场法的足球机器人路径规划系统[D].长春:长春理工大学,2007.
[17]王沛栋,冯祖洪,孙志长.一种栅格模型下机器人路径规划的改进蚁群体算法[D].计算机应用, 2008,28(11):2877~2880.
[18]程拥强,杨鹏,杨毅,等.用势场法改进的极限环导航方法在移动机器人中的应用[J].机器人,2004,26(2):133~138
[19]吴晓涛,孙曾忻,邓志东.基于网络结构的并行路径规划算法[J].清华大学学报(自然科学版),1996,36(5):67~71
[19]成伟明,唐振民,赵春霞,陈得宝.基于神经网络和PSO的机器人路径规划研究[J].系统仿真学报, 2008,20(3):608~611
[20] Kazuo sugibara, John Smith, Genetic algorithms for adaptive mothion planning of autonomous mobile robots[A],Problems IEEE Trans SMC[C].USA:SIM,1997
[21]王丽.移动机器人路径规划方法研究[D].西安:西北工业大学,2007
[22] Analysis of motor control and behavior in multi agent systems by means of artificial neural networds. Clinical Biomechanics 2005,Vol.20(2):19~125
[23]梁毓明,徐立鸿.移动机器人路径规划技术的研究现状与发展趋势[J].学术.论文.2009,3(1): 35~38
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