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GA-based learning in behaviour based robotics

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4 Author(s)
Dongbing Gu ; Dept. of Comput. Sci., Essex Univ., Colchester, UK ; Huosheng Hu ; J. Reynolds ; E. Tsang

This paper presents a genetic algorithm (GA) approach to evolving robot behaviors. We use fuzzy logic controllers (FLCs) to design robot behaviors. The antecedents of the FLCs are pre-designed, while their consequences are learned using a GA. The Sony quadruped robots are used to evaluate proposed approaches in the robotic football domain. Two behaviors, ball-chasing and position-reaching, are studied and implemented. An embodied evolution scheme is adopted, by which the robot autonomously evolves its behaviors based on a layered control architecture. The results show that the robot behaviors can be automatically acquired through the GA-based learning of FLCs.

Published in:

Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on  (Volume:3 )

Date of Conference:

16-20 July 2003