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A behavior based control and learning approach to real robots

Gu, D and Liu, J and Hu, H (2009) 'A behavior based control and learning approach to real robots.' Studies in Computational Intelligence, 177. 171 - 186. ISSN 1860-949X

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Abstract

Programming a real robot to do a given task in unstructured dynamic environments is very challenge. Incomplete information, large learning space, and uncertainty are major obstacles for control in real robots. When programming a real robot in unstructured dynamic environments, it is impossible to predict all the potential situation robots may encounter and specify all robot behaviors optimally in advance. Robots have to learn from, and adapt to their operating environment. In this chapter, we propose to use fuzzy logic to design robot behaviors and use a Markov decision process to model the coordination mechanism in the control and learning of real autonomous robotic systems. Based on the model, a Q-learning approach can be used to learn the behavior coordination. Two real robot applications are implemented by using such an approach, one is a Sony quadruped robot for soccer playing and another is a robotic fish for entertainment. Real robot testing results are provided to verify the proposed approach. © 2009 Springer-Verlag Berlin Heidelberg.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Clare Chatfield
Date Deposited: 20 Oct 2012 13:49
Last Modified: 17 Aug 2017 18:08
URI: http://repository.essex.ac.uk/id/eprint/3888

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