Fuzzy Q-Learning Integration for RoboSoccer Goal Keeper with Vision Tracking Algorithm

Dec 12, 2024

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This study presents an integration of fuzzy Q-learning in RoboSoccer for the goal keeper using inputs such as distance to ball, offset heading, and a vision tracking algorithm for out-of-sight scenarios. It proposes FIS update rules and error calculation methods for optimal performance. The exploration-exploitation technique combines mixed search strategies for improved decision-making.

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Fuzzy Q-Learning Integration for RoboSoccer Goal Keeper with Vision Tracking Algorithm

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Fuzzy Q-Learning Integration toRoboSoccer Presented by Alp Sardağ

Inputs for Goal Keeper FIS • Distance to ball • Offset Heading • In case the ball not in the region of sight, the location tracking algorithm will provide the necessary info.
FIS
FIS Update Rule The ideal form of error calculation: The approximated error:
FIS Update Rule Both update rules are Widrow-Hoff rule:
Exploration-Exploitation Technique • Mixed search : directed+undirected
Undirected Part Reducing sf will reduce the undirected part.
Directed Part