Abstract
An adaptive navigation control problem is presented for a quadruped robot in cluttered environments, by incorporating the capability of adaptive resonance theory (ART) in stable category recognition into fuzzy logic control. An ART-based neural network is introduced as an environment identifier for the purpose of adaptive selection of the adequate rule base for a fuzzy controller. Therefore, the proposed adaptive control scheme for the navigation of the robot is implemented by the adaptive fuzzy rule base in response to changes of the robot's environment, which can be fine observed by the proposed environment identifier. Some simulation results are presented to illustrate the proposed algorithm.
| Original language | English |
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| Pages | 626-631 |
| Number of pages | 6 |
| Publication status | Published - 2000 |
| Externally published | Yes |
| Event | 26th Annual Conference of the IEEE Electronics Society IECON 2000 - Nagoya, Japan Duration: Oct 22 2000 → Oct 28 2000 |
Other
| Other | 26th Annual Conference of the IEEE Electronics Society IECON 2000 |
|---|---|
| Country/Territory | Japan |
| City | Nagoya |
| Period | 10/22/00 → 10/28/00 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering