Evolving Connectionist System Based Role Allocation for Robotic Soccer

Abstract

Robotic soccer is an intelligent system where a group of mobile robots are controlled to perform soccer play (http://www.fira.net). The allocation of a suitable role for each robot in a team is a key for the success of the play. The paper treats this issue as one of pattern classification, and solves it with an Evolving classification function (ECF), a special evolving connectionist system (ECOS). A robot's role is determined by and evolves with the states of system ( robots and target ) in real time. The software and hardware platforms are set up for data collection and learning. The effectiveness of the proposed approach is verified by the experimental studies.

Keywords

• Robotic Soccer
• Mobile Robots
• Evolving Connectionist Systems