共查询到18条相似文献,搜索用时 125 毫秒
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机器人足球世界杯比赛(RoboCup)作为多智能体系统的一个良好的实验平台,已经成为人工智能的研究热点。本文综述了RoboCup机器人足球赛的发展概况和中型组比赛的现状,针对中型组足球机器人基于动态目标驱动模型的系统化、模块化软件系统架构和相关关键技术进行较为详细的分析和比较,最后对中型组机器人足球未来的发展方向进行了分析和展望。 相似文献
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RoboCup机器人足球比赛作为在世界上最有影响力的机器人赛事之一,备受推崇。同时作为多智能体研究的标准实验任务,已经成为人工智能的研究焦点。本文综述了RoboCup机器人足球赛的发展概况和小型组足球机器人系统,对小型组足球机器人的各子系统和相关关键技术进行较为详细的分析和比较,最后对小型组机器人足球技术的发展趋势进行了分析和展望。 相似文献
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中型组足球机器人挑球系统的设计 总被引:1,自引:0,他引:1
中型组机器人足球比赛系统是进行多智能体研究的理想实验平台。中型组足球机器人有自己的“头脑”和“手脚”,后者就是它的挑球系统。设计了基于电磁原理的中型组足球机器人挑球系统,简化了系统设计,提高了系统性能,满足中型组足球机器人的控制要求。 相似文献
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《机器人技术与应用》2010,(1):18-21
2009年12月21-24日,RoboCup机器人大赛中国公开赛第一分区赛在上海举行。第一分区赛是全部五个分区赛中赛程最长的一个赛区,包括RoboCup机器人足球中型组、舞蹈机器人、双足竞步机器人和机器人游中国四个大项的比赛,其中机器人游中国是今年新设立的项目。这四个项目分别在上海大学和上海医疗器械高等专科学校举行。 相似文献
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RoboCup机器人足球仿真比赛开发设计 总被引:2,自引:0,他引:2
机器人世界杯足球锦标赛(TheRobotWorldCup),简称RoboCup,通过提供一个标准任务来促进分布式人工智能、智能机器人技术及其相关领域的研究与发展。该文在介绍RoboCup仿真环境的基础上,系统完整地介绍了客户端程序的开发设计流程,阐述了其中涉及到的一些主要问题和算法,最后简要综述目前国际上的典型高层算法结构。 相似文献
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RoboCup救援组比赛包括搜索和救援的应用,提供机器人在典型环境中执行能力的客观评价。本文从机械结构、控制系统、建图迭代算法和建图处理方法等方面介绍RoboCup救援组机器人系统的相关关键技术。 相似文献
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Self-localization is the basis to realize autonomous ability such as motion planning and decision-making for mobile robots, and omnidirectional vision is one of the most important sensors for RoboCup Middle Size League (MSL) soccer robots. According to the characteristic that RoboCup competition is highly dynamic and the deficiency of the current self-localization methods, a robust and real-time self-localization algorithm based on omnidirectional vision is proposed for MSL soccer robots. Monte Carlo localization and matching optimization localization, two most popular approaches used in MSL, are combined in our algorithm. The advantages of these two approaches are maintained, while the disadvantages are avoided. A camera parameters auto-adjusting method based on image entropy is also integrated to adapt the output of omnidirectional vision to dynamic lighting conditions. The experimental results show that global localization can be realized effectively while highly accurate localization is achieved in real-time, and robot self-localization is robust to the highly dynamic environment with occlusions and changing lighting conditions. 相似文献
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This article introduces a navigation method for nonholonomic (differential drive) vehicles, based on odometry, regularly reset by a vision-based self-localization algorithm, and endowed with a sonar-based obstacle avoidance and guidance control algorithm that does not rely on path planning. The guidance controller is used in the soccer robots of the RoboCup middle-size league (MSL) ISocRob team, fully integrated in the state machine that coordinates task execution. The algorithm can be generally applied to structured indoor environments, provided that visual features can be observed by the self-localization method and that the visual information is not ambiguous. 相似文献
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RoboCup is an increasingly successful attempt to promote the full integration of AI and robotics research. The most prominent feature of RoboCup is that it provides the researchers with the opportunity to demonstrate their research results as a form of competition in a dynamically changing hostile environment, defined as the international standard game definition, which the gamut of intelligent robotics research issues are naturally involved. This article describes what we have learned from the past RoboCup activities, mainly the first and the second RoboCups, and overviews the future perspectives of RoboCup in the next century. First, the issue on what and why RoboCup is addressed, and a wide range of research issues are explained. Next, the current leagues are introduced and the research achievements are reviewed from a viewpoint of system architecture. Some of these achievements are included in this special issue. Finally, prospects for future activities are discussed. 相似文献
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基于RANSAC和Kalman滤波的足球机器人球速估计算法 总被引:1,自引:0,他引:1
针对中型组足球机器人如何有效地估计足球速度的问题,提出了一种基于Kalman滤波和RANSAC算法的新方法。首先对存储的若干帧足球位置信息作Kalman滤波,接着利用这些足球位置信息,建立若干个可能的足球速度模型并运用随机采样一致(RANSAC)算法选出最优的速度模型作为速度值。实验结果验证了该算法的有效性,同时由于RANSAC算法可以有效地去除外点的干扰,因此当足球位置信息具有较大噪声时,该方法可以较准确地估计足球的速度,较以往球速估计的算法具有更高的鲁棒性。 相似文献
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Marsella Stacy Tambe Milind Adibi Jafar Al-Onaizan Yaser Kaminka Gal A. Muslea Ion 《Autonomous Agents and Multi-Agent Systems》2001,4(1-2):115-129
Increasingly, multi-agent systems are being designed for a variety of complex, dynamic domains. Effective agent interactions in such domains raise some of the most fundamental research challenges for agent-based systems, in teamwork, multi-agent learning and agent modelling. The RoboCup research initiative, particularly the simulation league, has been proposed to pursue such multi-agent research challenges, using the common testbed of simulation soccer. Despite the significant popularity of RoboCup within the research community, general lessons have not often been extracted from participation in RoboCup. This is what we attempt to do here. We have fielded two teams, ISIS97 and ISIS98, in RoboCup competitions. These teams have been in the top four teams in these competitions. We compare the teams, and attempt to analyze and generalize the lessons learned. This analysis reveals several surprises, pointing out lessons for teamwork and for multi-agent learning. 相似文献
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模拟机器人足球比赛(Robot World Cup,RoboCup)作为多Agent系统的一个理想的实验平台,已经成为人工智能的研究热点。传统的Q学习已被有效地应用于处理RoboCup中传球策略问题,但是它仅能简单地离散化连续的状态、动作空间。提出将神经网络应用于Q学习,系统只需学习部分状态-动作的Q值即可获得近似连续的Q值,就可以有效地提高泛化能力。然后将改进的Q学习应用于优化传球策略,最后在RobCup中实现测试了该算法,实验结果表明改进的Q学习在RoboCup传球策略中的应用,可以有效提高传球的成功率。 相似文献