Abstract
The evolutionary particle swarm optimization (PSO) learning algorithm with the image processing technology is proposed to efficiently generate the fuzzy systems for achieving the control adaptability of the embedded mobile robot. The omni-directional image model of the mobile robot system is established to represent the entire tracking environment. The fuzzy control rules are automatically extracted by the defined flexible fitness function for multiple objectives in avoiding obstacles, selecting suitable fuzzy rules and approaching toward the desired targets at the same time. The illustrated examples with various initial positions and different blocks sizes are demonstrated that the selected fuzzy rules can overcome the obstacles and achieve the targets as soon as possible.
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© 2011 Springer-Verlag Berlin Heidelberg
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Chen, HC., Feng, HM., Guo, Dh. (2011). Evolutionary Learning Mobile Robot Fuzzy Systems Design. In: Zhu, M. (eds) Electrical Engineering and Control. Lecture Notes in Electrical Engineering, vol 98. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21765-4_4
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DOI: https://doi.org/10.1007/978-3-642-21765-4_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21764-7
Online ISBN: 978-3-642-21765-4
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