Abstract
Recently, intelligent control is being widely studied in the filed of robotics. A construction method of intelligent control system is the fuzzy behavior-based control which decomposes a task into each elemental behavior like a subsumption architecture, and each elemental behavior is realized by a fuzzy reasoning. In this paper, a module learning method is proposed for such a system, because the robot will be able to get more general knowledge or fuzzy reasoning than a central learning method. In particular, the module learning method is applied for an obstacle avoidance problem of a mobile robot. The effectiveness of the present method is illustrated through some simulations.
| Original language | English |
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| Pages | 454-459 |
| Number of pages | 6 |
| Publication status | Published - Dec 1 1999 |
| Externally published | Yes |
| Event | 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots whith High Intelligence and Emotional Quotients' - Kyongju, South Korea Duration: Oct 17 1999 → Oct 21 1999 |
Other
| Other | 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots whith High Intelligence and Emotional Quotients' |
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| City | Kyongju, South Korea |
| Period | 10/17/99 → 10/21/99 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications