Title
Gait control of hexapod walking robots using mutual-coupled immune networks
Abstract
Biological information processing systems can be said to be one of the ultimate decentralized systems and have been expected to provide various fruitful ideas to engineering fields, especially robotics. Among these systems, brain-nervous and genetic systems have already been widely used in modeling as neural networks and genetic algorithms, respectively. On the other hand, the immune system also plays an important role in coping with a dynamically changing environment by constructing self-non-self recognition networks among different species of antibodies. This system has many interesting features such as learning, self-organizing abilities, etc., viewed from the engineering standpoint. Therefore, it can be expected to provide novel approaches to the PDP paradigm. However, the immune system has not yet been applied to engineering fields. In this paper, we propose a new hypothesis concerning the structure of the immune system, called the mutual-coupled immune networks hypothesis, based on recent studies on immunology. We apply this idea to gait acquisition of a hexapod walking robot as a practical example. Finally, the feasibility of our proposed method is confirmed by simulations.
Year
DOI
Venue
1995
10.1163/156855396X00309
ADVANCED ROBOTICS
Keywords
Field
DocType
decentralized system,immune system,neural network,genetics,information processing,genetic algorithm,self organization
Artificial immune system,Information processing,Artificial intelligence,Engineering,Control system,Artificial neural network,Robot,Hexapod,Robotics,Genetic algorithm
Journal
Volume
Issue
ISSN
10
2
0169-1864
Citations 
PageRank 
References 
2
0.48
4
Authors
5
Name
Order
Citations
PageRank
Akio Ishiguro132160.94
Satoru Kuboshiki230.92
Shingo Ichikawa3122.62
Shingo Ichikawa4122.62
Yoshiki Uchikawa545572.31