DocumentCode :
3521937
Title :
Self-tuning fuzzy logic controller for reactive navigation
Author :
Mondelli, G. ; Castellano, G. ; Attolico, G. ; Stella, E. ; Distante, A.
Author_Institution :
Istituto Elaborazione Segnali ed Immagini, CNR, Bari, Italy
fYear :
1996
fDate :
19-20 Sep 1996
Firstpage :
87
Lastpage :
92
Abstract :
Low-level tasks for the navigation of autonomous vehicles can be accomplished efficiently by behavioral-based approaches mapping sensory data onto control commands in a reactive way, without using internal representations. Such a direct mapping can be usefully realized using fuzzy logic. All the choices involved in fuzzy controller design, impacting the final result in terms of complexity and performance, are generally made intuitively and/or by trial-and-error processes. Automatic learning and self-tuning of rules are required for adaptive controllers operating in real dynamic environments instead. This paper presents a method for minimizing the number of rules in a fuzzy controller without affecting its overall performance. The experiments have been made reducing the number of rules of a fuzzy controller developed for driving a TRC Labmate based vehicle along the wall on its right-hand side mapping ultrasonic sensor readings onto steering velocity values. Fuzzy rules have been learned automatically from training data collected during operator-driven runs of the vehicle. Experimental results, comparing the original and the optimized versions of the controller successfully driving the vehicle along arbitrarily shaped walls in real unknown environments, are provided
Keywords :
fuzzy control; mobile robots; navigation; path planning; TRC Labmate based vehicle; adaptive controllers; automatic learning; autonomous vehicles; behavioral-based approaches; control commands; low-level tasks; reactive navigation; real dynamic environments; self-tuning fuzzy logic controller; sensory data; ultrasonic sensor readings; Adaptive control; Automatic control; Fuzzy control; Fuzzy logic; Mobile robots; Navigation; Programmable control; Remotely operated vehicles; Vehicle driving; Vehicle dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 1996., Proceedings of the 1996 IEEE
Conference_Location :
Tokyo
Print_ISBN :
0-7803-3652-6
Type :
conf
DOI :
10.1109/IVS.1996.566358
Filename :
566358
Link To Document :
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