RoboCup: A Challenge Problem for AI and Robotics

  title={RoboCup: A Challenge Problem for AI and Robotics},
  author={Hiroaki Kitano and Minoru Asada and Yasuo Kuniyoshi and Itsuki Noda and Eiichi Osawa and Hitoshi Matsubara},
  booktitle={Robot Soccer World Cup},
RoboCup is an attempt to foster AI and intelligent robotics research by providing a standard problem where wide range of technologies can be integrated and examined. The first RoboCup competition was held at IJCAI-97, Nagoya. In order for a robot team to actually perform a soccer game, various technologies must be incorporated including: design principles of autonomous agents, multi-agent collaboration, strategy acquisition, real-time reasoning, robotics, and sensorfusion. RoboCup is a task for… 

The RoboCup Challenge

RoboCup as a strategic initiative to advance technologies

While the practical issues have been mainly attacked in the real robot leagues, the more strategic issues in multi-agent environments have been focused in the simulation league, such as teamwork among agents, agent modeling, and multi- agent learning which are argued in the rest of the paper.

PII: S0921-8890(99)00033-0

Technical challenges involved in RoboCup are described, a report of RoboCUP-97 mainly focusing on real robot competitions, and future perspectives are presented.

A Distributed Multiagent System for RoboCup

Experimental results show that the proposed architecture renders reasonable real time response so as to face the challenges posed in the RoboCup Small-Size Robot League.

A Review of Robot World Cup Soccer Research Issues RoboCup: Today and Tomorrow

What the authors have learned from the past RoboCup activities, mainly the first and the second RoboCups, are described, and the future perspectives of RoboCUP in the next century are overviewed.

Optimizing Simulated Humanoid Robot Skills

This thesis aims to improve the performance of motor skills such as getting up, kicking the ball and walking developed by the FC Portugal3D team by applying to them an automated optimization process, providing skills that performed much better than the original skills, additionally comparing favorably with other teams in the RoboCup 3D simulated league.

The RoboCup Synthetic Agent Challenge 97

This paper presents three specific challenges for the next two years of RoboCup Challenge: learning of individual agents and teams; multi-agent team planning and plan-execution in service of teamwork; and opponent modeling.

A new agent architecture for RoboCup tournament: cognitive architecture

  • Shi LiZhen YeZengqi-Sun
  • Computer Science
    Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393)
  • 2000
A new type of agent architecture-cognitive architecture-is proposed and a robot soccer team underlying this framework is established, to enable the intelligent robots possess the same structures as the authors' brain and to develop the functions for each module to improve the intelligence of the robots.

Distributed Coordination in Heterogeneous Multi-Robot Systems

An approach to distributed coordination of a multi-robot system that is based on dynamic role assignment that has been successfully implemented within the team of heterogeneous robots Azzurra Robot Team in a very dynamic hostile environment provided by the RoboCup robotic soccer competitions.

Multi-Robot Systems: A classication focused on coordination

A survey of the recent work in the area of multi-Robot Systems is presented by specically examining the forms of cooperation and coordination realized in the MRS and a new taxonomy for classication of the approaches to coordination is proposed.



Reactive Deliberation: An Architecture for Real-Time Intelligent Control in Dynamic Environments

The results suggest that the architectural elements in reactive deliberation are sufficient for real-time intelligent control in dynamic environments.

Introducing the Tileworld: Experimentally Evaluating Agent Architectures

The hypothesis is that the appropriateness of a particular meta-level reasoning strategy will depend in large part upon the characteristics of the environment in which the agent incorporating that strategy is situated.

Tracking Dynamic Team Activity

To facilitate real-time ambiguity resolution with team models, aspects of tracking are cast as constraint satisfaction problems to exploit constraint propagation techniques and a cost minimality criterion is applied to constrain tracking search.

A robust layered control system for a mobile robot

  • R. Brooks
  • Computer Science
    IEEE J. Robotics Autom.
  • 1986
A new architecture for controlling mobile robots is described, building a robust and flexible robot control system that has been used to control a mobile robot wandering around unconstrained laboratory areas and computer machine rooms.

Rapid Task Learning for Real Robots

This chapter discusses how learning can be speeded up by exploiting properties of the task, sensor configuration, environment, and existing control structure.

Behavior coordination for a mobile robot using modular reinforcement learning

  • E. UchibeM. AsadaK. Hosoda
  • Computer Science
    Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96
  • 1996
A method of modular learning which coordinates multiple behaviors taking account of a trade-off between learning time and performance is presented, applied to one to one soccer playing robots.

Situated agents can have goals

  • P. Maes
  • Business
    Robotics Auton. Syst.
  • 1990

Commitment and Effectiveness of Situated Agents

The results demonstrate the feasibility of developing systems for empirical measurement of agent performance that are stable, sensitive, and capable of revealing the effect of "high-level" agent characteristics such as commitment.

A Metalevel Coordination Strategy for Reactive Cooperative Planning

A metalevel coordination strategy to implement an adaptive organization for reactive cooperative planning that changes its organizational scheme adaptively as a means of coping with the dynamic problem spaces and works efficiently in cases where the communication cost is relatively expensive.

Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function

A Memory-based technique for to choose an action based on a continuous-valued state attribute indicating the position of an opponent, investigating the question of how an agent performs in nondeterministic variations of the training situations.