Title
Adapting Real Mobile Robots To Complex Environments Using A Pattern Association Network Controller (Pan-C)
Abstract
Adapting real mobile robots to complex or dynamic environments is just one of the many challenges robotics researchers face. The difficulty in such environments is in developing a simple, quick adaptive controller that adapts robots to patterns in these environments, especially when individual patterns require unique behavior from the robot. Although most standard evolutionary algorithms attempt to obtain optimal networks for such environments, this is difficult to attain due to network confusion in adapting and readapting patterns. We propose a simple adaptive controller able to learn and remember. It simplifies environments into simple groups of patterns, each of which the robot can independently learn and memorize. The memory introduced in the controller enhances the robot's ability to track its own experience and to cope with upcoming events. Experimental results show that the controller handles general complexity and gives the robot more adaptability, stability, and autonomy.
Year
DOI
Venue
2009
10.20965/jaciii.2009.p0312
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS
Keywords
DocType
Volume
adaptive controller, learning and memory, symmetrical neural network, pattern association network controller
Journal
13
Issue
ISSN
Citations 
3
1343-0130
1
PageRank 
References 
Authors
0.37
9
3
Name
Order
Citations
PageRank
Indra Bin Mohd Zin1192.33
Fady Alnajjar26612.23
Kazuyuki Murase3103875.66