39 research outputs found

    Individual and coordinated decision for the CAMBADA team

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    Mestrado em Engenharia de Computadores e TelemáticaA coordenação em sistemas multi-robô é um aspecto crucial no futebol robótico. A maneira como cada equipa coordena cada um dos seus robôs em acções cooperativas define a base da sua estratégia. Este trabalho tem como foco o desenvolvimento da coordenação e estratégia da equipa CAMBADA. CAMBADA é a equipa de futebol robótico da modalidade RoboCup Middle Size League da Universidade de Aveiro. Foi desenvolvida pelo grupo ATRI, pertencente µa unidade de investigação IEETA. O presente trabalho baseia-se em trabalho desenvolvido anteriormente, tentando melhorar o desempenho da equipa. Cada robô da equipa CAMBADA é um agente independente e autónomo capaz de coordenar as suas acções com os colegas de equipa através da comunicação e da partilha de informação. O comportamento de cada robô deverá ser integrado na estratégia global da equipa, resultando assim em acções cooperativas de todos os robôs. Isto é conseguido através do uso de papeis(roles) e comportamentos(behaviours) que definem a atitude de cada robô e as acções que daí resultam. Novos papeis foram desenvolvidos para complementar a estratégia de equipa, e alguns dos papeis existentes foram melhorados. Também foram efectuadas melhorias em alguns dos comportamentos existentes. É efectu- ada a descrição de cada um destes papeis e comportamentos, assim como as alterações efectuadas. O trabalho desenvolvido foi testado nas competições do Robótica 2008 (o desenvolvimento não estava ainda concluído) e por fim nas competições do RoboCup'2008. A participação da equipa no RoboCup'2008 é analisada e discutida. A equipa consagrou-se campeã mundial, vencendo a competição da Middle Size League do RoboCup'2008 em Suzhou, China. ABSTRACT: Multi-robot coordination is one crucial aspect in robotic soccer. The way each team coordinates its individual robots into cooperative global actions define the foundation of its strategy. CAMBADA is the RoboCup Middle Size League robotic soccer team of the University of Aveiro. It was created by the ATRI group, part of the IEETA research unit. This work is focused on coordination and strategy development for the CAMBADA team. It is built upon previous work and tries to improve the team performance further. In CAMBADA each robot is an independent agent, it coordinates its actions with its teammates through communication and information exchange. The resulting behaviour of the individual robot should be integrated into the global team strategy, thus resulting in cooperative actions by all the robots. This is done by the use of roles and behaviours that define each robot attitude in the field and resulting individual actions. In this work, new roles were created to add to the team strategy and some of the previous existing roles were improved. Some of the existing behaviours were also improved to better fit the desired goals. Each role and behaviour is described as well as the changes made. The resulting work was put to test in the portuguese Robotica 2008 competition (while still in progress) and finally in the RoboCup'2008 world competitions. The performance of the team in the latter is analysed and discussed. The team achieved the 1st place in the RoboCup'2008 MSL world competitions

    Coordination methodologies applied to RoboCup : a graphical definition of setplays

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    Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

    Modelo de estratégia e coordenação genérico para sistemas multi-agente

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    Estágio realizado na Universidade de Aveiro e orientado pelo Prof. Doutor Jose Nuno Panelas Nunes LauTese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

    RoboCup Soccer Leagues

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    RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics

    Applications of DEC-MDPs in multi-robot systems

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    International audienceOptimizing the operation of cooperative multi-robot systems that can cooperatively act in large and complex environments has become an important focal area of research. This issue is motivated by many applications involving a set of cooperative robots that have to decide in a decentralized way how to execute a large set of tasks in partially observable and uncertain environments. Such decision problems are encountered while developing exploration rovers, teams of patrolling robots, rescue-robot colonies, mine-clearance robots, et cetera.In this chapter, we introduce problematics related to the decentralized control of multi-robot systems. We rst describe some applicative domains and review the main characteristics of the decision problems the robots must deal with. Then, we review some existing approaches to solve problems of multiagent decen- tralized control in stochastic environments. We present the Decentralized Markov Decision Processes and discuss their applicability to real-world multi-robot applications. Then, we introduce OC-DEC-MDPs and 2V-DEC-MDPs which have been developed to increase the applicability of DEC-MDPs
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