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 |
| Publisher | Springer Verlag |
| Pages | 206-215 |
| Number of pages | 10 |
| ISBN (Print) | 3540633995, 9783540633990 |
| Publication status | Published - 1997 Jan 1 |
| 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 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Hybrid evolutionary learning of fuzzy logic and genetic algorithm. / Cho, Sung Bae; Lee, Seung Ik.
Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers. Springer Verlag, 1997. p. 206-215 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1285).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Hybrid evolutionary learning of fuzzy logic and genetic algorithm
AU - Cho, Sung Bae
AU - Lee, Seung Ik
PY - 1997/1/1
Y1 - 1997/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84947927450&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84947927450&partnerID=8YFLogxK
M3 - Conference contribution
SN - 3540633995
SN - 9783540633990
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 206
EP - 215
BT - Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers
PB - Springer Verlag
ER -