DocumentCode :
406255
Title :
A perceptual system for vision-based evolutionary robotics
Author :
Kubota, Naoyuki ; Niwa, Mizuki ; Azuma, Hiroaki ; Ueda, Atsushi
Author_Institution :
Dept. of Human & Artificial Intelligent Sytems, Fukui Univ., Japan
Volume :
1
fYear :
2003
fDate :
14-17 Dec. 2003
Firstpage :
841
Abstract :
This paper discusses the perceptual system of a mobile robot from the viewpoint of ecological psychology. The control of the mobile robot is based on the concept of perceiving-acting cycle. We discuss the perceptual system for extracting perceptual information that will be used and required for next action. Based on action outputs, the perceptual module is selected and accommodated in order to persist a specific perception. Furthermore, we apply a steady-state genetic algorithm (SSGA) for extracting perceptual information from an image. The average and divergence used for mutation in the SSGA for detecting a pattern are updated according to the accuracy of detection. The current searching result of SSGA is reflected to the next search of SSGA. In this way, the searching process of the perceptual system for the mobile robot is cyclic according to the spatio-temporal context of the environment. We apply the proposed method for the control of a mobile robot used under an office automation floor. Experimental results show the effectiveness of the proposed method.
Keywords :
genetic algorithms; mobile robots; office automation; robot vision; ecological psychology; mobile robot; office automation; perceiving-acting cycle; perceptual system; spatio-temporal context; steady-state genetic algorithm; vision-based evolutionary robotics; Artificial intelligence; Automatic control; Competitive intelligence; Data mining; Humans; Intelligent robots; Mobile robots; Robot sensing systems; Robot vision systems; Robotics and automation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
Type :
conf
DOI :
10.1109/ICNNSP.2003.1279407
Filename :
1279407
Link To Document :
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