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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ishiguro, A. Kuboshiki, S. Ichikawa, S. Uchikawa, Y. |
| Copyright Year | 1995 |
| Description | Author affiliation: Sch. of Eng., Nagoya Univ., Japan (Ishiguro, A.; Kuboshiki, S.; Ichikawa, S.; Uchikawa, Y.) |
| Abstract | Biological information processing systems are amongst the ultimate decentralized systems, and are expected to provide various fruitful ideas for engineering fields, especially robotics. Among these systems, the brain-nervous system and genetic system have already been widely used by modeling as neural networks and genetic algorithms, respectively. The immune system also plays an important role in coping with a dynamically changing environment by constructing self-nonself recognition networks among different species of antibodies. This system also has a lot of interesting features such as learning, self-organizing abilities and so on viewed from the engineering standpoint. However, the immune system has not yet been applied to engineering fields. We propose a new hypothesis concerning the structure of the immune system, called the mutual-coupled immune network 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. |
| Starting Page | 672 |
| Ending Page | 677 |
| File Size | 699125 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780327594 |
| DOI | 10.1109/ICEC.1995.487465 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1995-11-29 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Legged locomotion Robot kinematics Immune system Information processing Brain modeling Biological neural networks Computational Intelligence Society Biological system modeling Genetic algorithms Organisms |
| Content Type | Text |
| Resource Type | Article |
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