自主移动机器人足球比赛视觉定位方法综述

综述了RoboCup足球赛中全自主移动机器人基于视觉的定位技术,包括机器人自定位和多机器人协作物体定位.介绍了定位技术的发展情况与分类.从机器人环境构建形式的不同以及先验位姿和概率方法的应用与否等方面,系统地分析和比较了各种自定位方法.对于多机器人协作物体定位,阐述了静态方法和动态跟踪方法.总结了定位过程中需要重点研究的传感器模型构建、图像处理、特征匹配以及协作过程涉及的相关问题.最后就视觉定位存在的问题和技术发展趋势进行了讨论.     

RoboCup比赛环境下足球机器人路径规划研究

RoboCup中型组足球机器人比赛具有高度的对抗性和实时性．比赛中机器人需要针对不同的比赛态势进行角色切换和任务选择．在这种环境下，应用传统人工势场或一般改进型人工势场的路径规划方法都无法得到令人满意的结果．将障碍物与机器人之间的相对速度矢量以及目标与机器人之间的相对速度矢量分别引入人工势场法中，对传统的势场函数进行了改进；并根据机器人的不同角色和任务，采用模糊逻辑方法对势场函数进行修正，提出一种处理多角色多任务环境的改进型人工势场法机器人路径规划方法．仿真试验和实际应用验证了此算法存足球机器人比赛系统中的可行性．     

GOAALLL!: Using sentiment in the world cup to explore theories of emotion

Sporting events evoke strong emotions among fans and thus act as natural laboratories to explore emotions and how they unfold in the wild. Computational tools, such as sentiment analysis, provide new ways to examine such dynamic emotional processes. In this article we use sentiment analysis to examine tweets posted during 2014 World Cup. Such analysis gives insight into how people respond to highly emotional events, and how these emotions are shaped by contextual factors, such as prior expectations, and how these emotions change as events unfold over time. Here we report on some preliminary analysis of a World Cup twitter corpus using sentiment analysis techniques. After performing initial tests of validation for sentiment analysis on data in this corpus, we show these tools can give new insights into existing theories of what makes a sporting match exciting. This analysis seems to suggest that, contrary to assumptions in sports economics, excitement relates to expressions of negative emotion. The results are discussed in terms of innovations in methodology and understanding the role of emotion for “tuning in” to real world events. We also discuss some challenges that such data present for existing sentiment analysis techniques and discuss future analysis.     

激战RoboCup2006

2006年6月14日至20日,德国世界杯激战正酣的同时,来自全球36个国家的近440支队伍相聚在德国不来梅参加RoboCup2006即第十届机器人世界杯竞赛.     

Development of the multifunctional rescue robot FUHGA2 and evaluation at the world robot summit 2018

Abstract

Robots are needed in rescue activities and the inspection of infrastructure. We developed the rescue robot FUHGA2 so that it has various functions. FUHGA2 has high mobility, with main crawlers covering the body and four sub-crawlers, high dexterity using a long six-axis arm, and high searching ability using various sensors. Furthermore, a novel parallel gripper unit with wire-jamming mechanism is mounted at the tip of the arm, which can change its hardness and fit its shape to an object. Additionally, high Maneuvering is achieved by displaying sensor information to the operator clearly and intuitive operation command design. FUHGA2 won the World Robot Summit 2018 Standard Disaster Robotics Challenge, which is a competition for rescue robots. We achieved high scores in all categories of tasks. In this paper, we describe the development of FUHGA2 and the performance evaluation results from the World Robot Summit 2018.     

Global path planning for mobile robot with grid-type world model

This paper presents a new methodology for global path planning for an autonomous mobile robot in a grid-type world model. The value of a certainty grid representing the existence of an obstacle in the grid is calculated from readings of sonar sensors. In the calculation, a way of utilizing three sonar sensor readings at a time is introduced, resulting in a more accurate world model. Once the world model is obtained, a network for path planning is built by using the model. The global paths, defined as the shortest paths between all pairs of nodes in the network, are calculated. A fast algorithm using a decomposition technique is proposed for real-time calculation. The new methodology has been implemented on the mobile robot whose role is to transport materials in a flexible manufacturing system. The results show that the proposed method of certainty grids satisfactorily represents a precise environment, including the locations of obstacles. Thus, the robot successfully comprehends its surroundings, and navigates to its destinations along optimal paths.     

Sensory interactive robot trajectory control using a real-time world model

A major consideration in the design of sensory interactive trajectory generation software for a Flight Telerobotic Servicer (FTS) is the availability and maintenance of a current model of the manipulator's world. The NASA/NBS Standard Reference Model for Telerobot Control System Architecture (NASREM), which has been adopted by NASA for control of the FTS, provides a logical computing architecture for telerobotics. It defines a hierarchical control system in which complex tasks are decomposed into progressively simpler subtasks, or objectives. It contains a hierarchy of world modeling modules which maintain the system's internal model of the manipulator and its world by continuously updating the model based upon sensory data. Each world modeling module contains support processes or functions which simultaneously and asynchronously support sensory processing and task decomposition. This paper discusses the role of world modeling in support of trajectory generation and execution. For sensory interactive robot motion control, the world modeling modules must operate rapidly so that the model of the world remains in registration with the real world.This paper discusses the world modeling modules of a hierarchical control system which facilitate sensory interactive trajectories by decoupling and supporting the sensory and manipulator planning processes. We define the types of information which should be included in the interfaces to the modules, as well as the modules' structure and function. Finally, we discuss the real-time implementation and experimental results of a particular sensory interactive algorithm performed in our laboratory.     

Multiagent learning towards RoboCup

This article describes the issues in multiagent learning towards RoboCup,^1≈3) especially for the real robot leagues. First, the review of the issue in the context of the related area is given, then related works from several viewpoints are reviewed. Next, our approach towards RoboCup Initiative is introduced and finally future issues are given. Minoru Asada, Ph.D.: He received B.E., M.Sc., and Ph.D., degrees in control engineering from Osaka University, in 1977, 1979, and 1982, respectively. From 1982 to 1988, he was a research associate of Control Engineering, Osaka University. In 1989, he became an associate professor of Mechanical Engineering for Computer-Controlled Machinery, Osaka University. In 1995 he became a professor of the department of Adaptive Machine Systems at the same university. From 1986 to 1987, he was a visiting researcher of Center for Automation Research, University of Maryland, College Park, MD. He received the 1992 best paper award of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS92), and the 1996 best paper award of RSJ (Robotics Society of Japan). Also, his paper was one of the finalists of IEEE Robotics and Automation Society 1995 Best Conference Paper Award. He was a general chair of IEEE/RSJ 1996 International Conference on Intelligent Robots and Systems (IROS96). Since early 1990, he has been involved in RoboCup activities and his team was the first champion team with USC team in the middle size league of the first RoboCup held in conjunction with IJCAI-97, Nagoya, Japan. Eiji Uchibe, Ph.D.: He received a Ph.D. degree in mechanical engineering from Osaka University in 1999. He is currently a research associate of the Japan Society for the Promotion of Science, in Research for the Future Program titled Cooperative Distributed Vision for Dynamic Three Dimensional Scene Understanding. His research interests are in reinforcement learning, evolutionary computation, and their applications. He is a member of IEEE, AAAI, RSJ, and JSAI.     

非通讯多Agent协作在RoboCup中的应用

智能体的行为预测是多智能体系统中的一个具有挑战性的问题。根据多agent系统（MAS）中的研究，为了提高进攻的速度，文中将一种新的合作策略引入到机器人足球中。首先，介绍了MAS的特点。同时，引入了一种agent削减算法来进行行为决策。进一步，调整了涉及到的agent的数目，在非通讯情况下实现了球员之间的协作。以后工作的重点是增加对对手的建模，以期提高进攻的成功率。     

RoboCup 3D Server分析

RoboCup仿真比赛是MAS系统的理想测试平台,而3D仿真是RoboCup研究的热点。由于目前缺乏相关的资料,给参赛队增加了不少困难。本文将分析RoboCup 3D Sewer的一些关键技术,以期能让读者对这一新技术有一个全面的了解,缩短球队的开发过程。     

非通讯多Agent协作在RoboCup中的应用

智能体的行为预测是多智能体系统中的一个具有挑战性的问题。根据多agent系统(MAS)中的研究,为了提高进攻的速度,文中将一种新的合作策略引入到机器人足球中。首先,介绍了MAS的特点。同时,引入了一种agent削减算法来进行行为决策。进一步,调整了涉及到的agent的数目,在非通讯情况下实现了球员之间的协作。以后工作的重点是增加对对手的建模,以期提高进攻的成功率。     

基于角色的RoboCup足球策略

随着计算机软硬件技术的快速发展,人工智能的研究领域出现了一些新的机遇和挑战。未来50年中,人工智能的主要问题是“多主体动态不可预测环境中的问题求解”,其标准问题是足球的机-机对抗赛和人-机对抗赛。论文探讨了机器人足球Robocup仿真比赛的一些关键性技术,并提出了基于角色的决策方法。     

The road to RoboCup 2050

The ultimate goal of the RoboCup initiative is stated as follows: by mid-21st century, a team of fully autonomous humanoid robot soccer players shall win the soccer game, comply with the official rule of the FIFA, against the winner of the most recent World Cup. The authors consider this goal from the perspective of how close we are to it and what has to be done to reach it     

RoboCup中阵型策略的实现

机器人足球仿真比赛是检验各种多智能体系统理论的标准平台,在这个极为复杂的多智能体环境中,多个智能体需要通过协作完成共同目标,而协作可通过共享阵型获得.阵型是多智能体协作行为所要求的,它使多个智能体以有序、智能的方式进行协作.为适应RoboCup实时动态环境下多智能体间的协作需求,文中以阵型为研究对象,提出基于不同阵型转换和基于单一阵型调整的阵型策略并将其应用到机器人足球仿真比赛中,仿真结果表明结合应用这两种阵型策略提高了仿真球队的协作攻防效果.