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Abstract. This paper provides an investigation on the aplicability of the color classification using an artificial neural network in the robotic soccer domain. Using the well known network generalization propriety, the aplicability of the approach to the segmentation of colored images over the RGB

system in the robot soccer domain. The details of the Essex Wizards robot football team and its control system are described. A real-time visual tracking algorithm has been developed. Some initial results of the image pre-processing and visual tracking algorithms in real environment setting

and for acquiring new cases. The work pre-sented in this paper addresses these two goals: to find out the “right ” scope of existing cases and to introduce new cases when no appropriate solution is found. We have tested the mechanism in the robot soccer domain performing experiments, both under simulation

and for acquiring new cases. The work presented in this paper addresses these two goals: to find out the “right ” scope of existing cases and to introduce new cases when no appropriate solution is found. We have tested the mechanism in the robot soccer domain performing experiments, both under simulation

Abstract — This paper addresses the problem of colour recognition in real time computer vision systems applied to the robot soccer domain. The developed work presents a novel combination between our current model-based computer vision system and neural networks to classify colours and identity

Abstract. This work proposes a novel approach for introducing market-driven strategy to robot soccer domain in order to solve vital issues related to multiagent coordination. In robot soccer, two teams of robots compete with each other to win the match. For the benefit of the team, the robots

Abstract. This paper proposes a set of practical extensions to the vision-based Monte Carlo localization for RoboCup Sony AIBO legged robot soccer domain. The main disadvantage of AIBO robots is that they have a narrow field of view so the number of landmarks seen in one frame is usually not enough

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The paper presents an algorithm for multi-agent strategic modeling (MASM). The method applies domain knowledge and transforms sequences of basic multi-agent actions into a set of strategic action descriptions in the form of graph paths, agent actions, roles and corresponding rules. The rules