Soccer robot system is a typical multi-agent system and multi-robot cooperative system.
足球机器人比赛是多智能体系统研究的一个新的标准问题。
This paper focuses on the hierarchical learning of high level strategy of soccer robot system.
本文集中研究足球机器人高层策略的分层学习。
Soccer robot system is a perfect platform in research and application of artificial intelligence.
足球机器人系统是人工智能技术的一个非常好的应用与研究平台。
In this paper, the main research on system software design and path planning fur soccer robot system is introduced.
本文以足球机器人系统为研究背景，主要对该系统软件设计和路径规划进行研究。
Secondly, some design patterns which are used in the development of soccer robot system are analyzed and summarized.
其次，分析了在足球机器人系统软件中运用到的一些设计模式。
The dynamic track and identification to the color-ball in soccer robot system based on vision is the most important task.
在基于视觉的足球机器人系统中，对场上焦点目标——球的动态跟踪识别是系统设计的第一要务。
A soccer robot system consists of four modules: cart subsystem, communication system, decision subsystem and vision subsystem.
足球机器人系统可分为四大模块：小车子系统、通讯子系统、决策子系统与视觉子系统。
According to the study and analysis of soccer robot system, fuzzy method is introduced to describe the complex state space of soccer robot.
通过对足球机器人系统的分析和研究，使用模糊手段描述了复杂的足球机器人状态空间；
After analyzing the demand of vision system in large league, a new set of vision system was designed for centralized control soccer robot system of large league.
分析了大场地条件下对视觉系统的要求，设计了一套新颖的大场地集控式足球机器人视觉系统。
Based on the above theories and technological achievements, research and design of integrated centralized control soccer robot system of large league was completed.
在以上理论和技术研究成果的基础上，完成了完整的大场地集控式足球机器人系统的研究和设计。
Soccer robot system is a dynamic, uncertain and real-time platform, and in such an adversarial and competitive environment, how to realize the real-time robot path-planning is a challenge problem.
机器人足球系统环境是一个具有动态性、不确定性、实时性的环境，在这样一个具有高度实时性和竞争性平台上研究路径规划也是一个很有挑战性的课题。
In his paper, deep research is made on the soccer robot system of large league and solve a series of critical problems of technology from theory to practice, finally design and realize the system.
本文深入研究了大场地集控式足球机器人系统，从理论到实践解决了这一系统的关键技术问题，设计并实现了该系统。
Based on soccer robot simulation as its research platform, this paper studies the learning of high level strategy of multi-agent adversarial system.
本文以足球仿真机器人系统为研究平台，研究多智能体对抗系统的高层策略学习问题。
Robot soccer match system is a typical multi-agent cooperation system; therefore it is a standard platform for researching multi-agent cooperation problem.
机器人足球比赛系统是典型的多智能体协作系统，是研究多智能体协作问题的标准平台。
The experiments show that it has completed the function of FIRA's ROBOSOT(autonomous soccer robot )vision system.
实验表明系统很好实现了FIRA的ROBOSOT（自主式足球机器人）视觉系统的功能。
With the soccer robot vision system as studied object, a set of methods of recognition of color mark is proposed.
以足球机器人视觉系统为研究对象，提出了一套基于颜色信息的色标识别方法。
To gain excellent efficiency of role assignment in robot soccer strategy system, a role assignment algorithm based on combinatorial optimization is presented.
为了在机器人足球策略系统中获得良好的角色分配效率，提出了基于组合最优的角色分配算法。
We have made a research on Omni-vision System, which is used by autonomous soccer robot, and Omni-vision System is involved in Image Processing, Image Analysis, Image Understanding, etc.
本文的研究内容是应用于全自主足球机器人的全维视觉系统，全维视觉系统涉及图像处理、图像分析和图像理解等多个门类的知识。
Vision system is an important part of the whole robot soccer system.
视觉系统是整个机器人足球系统的重要组成部分。
The simulation system includes simulation of the real world, design of decision system and animation design. It can demonstrate vividly the competitive scene of robot soccer tournaments.
该仿真系统包括对现实世界的仿真、决策系统设计和动画设计，能够生动地再现机器人足球比赛的激烈场面。
Quick and correct recognition of the ball and the robots is the foundation of decision system in robot soccer game which is an integrated competition activity based on high technology.
在机器人足球比赛这项综合性的高技术对抗活动中，快速准确地识别足球和机器人是决策系统的基础。
Based on the characteristics of the robot soccer vision system, an algorithm using Run Length Encoding (RLE) for real-time image processing is presented.
根据机器人足球视觉系统的特点，提出基于游程长度编码(RLE)的实时快速图像处理算法。
Firstly, this paper analyses the design requirement of soccer robot bottom control system, and frames a system designed project using ARM micro as the kernel.
首先，分析了足球机器人底层控制系统的设计要求，制定了以ARM微处理器为核心的系统设计方案。
The experimental platform for function system of robot soccer was built in laboratory of college, which demonstrates the function of vision, decision, communication and action of robot soccer system.
在高校实验室中构建足球机器人功能系统的实验平台，该平台能展现足球机器人系统的视觉、决策、通信和车体动作等功能。
In order to improve the movement performance of soccer robots, the control parameter integrated decision system for robot soccer is discussed.
为了提高足球机器人的运动性能，设计了足球机器人控制参数整定系统。
Robot soccer match system is a typical multi-agent cooperation system; therefore it is a standard platform for researching in multi-agent cooperation problems.
机器人足球比赛系统是典型的多智能体协作系统，是研究多智能体协作问题的标准平台。
Finally, the software system of the autonomous soccer robot, is studied and designed, which achieved a calibration environment, color sampling, target identification and testing feedback module.
本文最后研究并设计了全自主式足球机器人的软件系统，该系统实现了环境标定、颜色信息采样、目标识别和测试反馈等功能模块。
The soccer robot strategy system based on evolutionary methods to improve the intelligence of soccer robot strategy system.
为了提高足球机器人策略系统的智能，提出了基于进化方法的足球机器人策略系统。
This paper gives the method of the shortest path for obstacle avoidance of robot soccer in the multigent system based on the method of complex of optimization.
该文基于最优化方法中的复形法，对多智能体领域里的机器人足球避障问题，给出了最短路径的解决方法。
This paper gives the method of the shortest path for obstacle avoidance of robot soccer in the multigent system based on the method of complex of optimization.
该文基于最优化方法中的复形法，对多智能体领域里的机器人足球避障问题，给出了最短路径的解决方法。
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