Abstract
This paper presents a hybrid method of fuzzy logic and genetic algorithm as promising model for evolutionary system, which controls a mobile robot effectively. The system obtains sensory information from eight infrared sensors and operates the robot with two motors driven by fuzzy inference based on the sensory information. Genetic algorithm has been utilized to robustly determine the shape and number of membership functions in fuzzy rules. Through the simulation with a simulated robot called Khepera, we assure ourselves that the evolutionary approach finds a set of optimal fuzzy rules to make the robot reach the goal point, as well as to solve autonomously several subproblems such as obstacle avoidance and passing-by narrow corridors.
| Original language | English |
|---|---|
| Title of host publication | Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers |
| Editors | Xin Yao, Jong-Hwan Kim, Takeshi Furuhashi |
| Publisher | Springer Verlag |
| Pages | 206-215 |
| Number of pages | 10 |
| ISBN (Print) | 3540633995, 9783540633990 |
| DOIs | |
| Publication status | Published - 1997 |
| Event | 1st Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1996 - Taejon, Korea, Republic of Duration: 1996 Nov 9 → 1996 Nov 12 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 1285 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 1st Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1996 |
|---|---|
| Country | Korea, Republic of |
| City | Taejon |
| Period | 96/11/9 → 96/11/12 |
Bibliographical note
Publisher Copyright:© Springer-Verlag Berlin Heidelberg 1997.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)