Anam, Khairul (2009) EMBEDDED LEARNING ROBOT WITH FUZZY Q-LEARNING FOR OBSTACLE AVOIDANCE BEHAVIOR. Industrial Electronic Seminar.
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Abstract
Fuzzy Q-learning is extending of Q-learning algorithm that uses fuzzy inference system to enable Q-learning holding continuous action and state. This learning has been implemented in various robot learning application like obstacle avoidance and target searching. However, most of them have not been realized in embedded robot. This paper presents implementation of fuzzy Q-learning for obstacle avoidance navigation in embedded mobile robot. The experimental result demonstrates that fuzzy Q-learning enables robot to be able to learn the right policy i.e. to avoid obstacle.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Ms Mellissa Andayani |
| Date Deposited: | 15 Mar 2011 19:19 |
| Last Modified: | 31 Mar 2011 22:40 |
| URI: | http://repo.pens.ac.id/id/eprint/102 |
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