Abstract
This paper presents an approach for evolving optimum behaviors for a nonholonomic mobile robot in a class of dynamic environments. A new evolutionary algorithm reflecting some powerful features in the natural evolutionary process to have flexibility to deal with changes in the environment is used to evolve optimum behaviors. Furthermore, a fuzzy set based multi-objective fitness evaluation function is adopted in the evolutionary algorithm. The multi-objective evaluation function is designed so that it allows incorporating complex linguistic features that a human observer would desire in the behaviors of the mobile robot movements. To illustrate the effectiveness of the proposed method, simulation results are compared using a conventional evolutionary algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 255-277 |
| Number of pages | 23 |
| Journal | Journal of Intelligent and Robotic Systems: Theory and Applications |
| Volume | 32 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Nov 2001 |
| Externally published | Yes |
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Keywords
- Dynamic environments
- Evolutionary algorithms
- Fuzzy behavior based control
- Fuzzy set based objective functions
- Nonholonomic mobile robot
ASJC Scopus subject areas
- Control and Systems Engineering
- Artificial Intelligence
Cite this
Evolutionary learning of a fuzzy behavior based controller for a nonholonomic mobile robot in a class of dynamic environments. / Nanayakkara, D. P Thrishantha; Watanabe, Keigo; Kiguchi, Kazuo; Izumi, Kiyotaka.
In: Journal of Intelligent and Robotic Systems: Theory and Applications, Vol. 32, No. 3, 11.2001, p. 255-277.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Evolutionary learning of a fuzzy behavior based controller for a nonholonomic mobile robot in a class of dynamic environments
AU - Nanayakkara, D. P Thrishantha
AU - Watanabe, Keigo
AU - Kiguchi, Kazuo
AU - Izumi, Kiyotaka
PY - 2001/11
Y1 - 2001/11
N2 - This paper presents an approach for evolving optimum behaviors for a nonholonomic mobile robot in a class of dynamic environments. A new evolutionary algorithm reflecting some powerful features in the natural evolutionary process to have flexibility to deal with changes in the environment is used to evolve optimum behaviors. Furthermore, a fuzzy set based multi-objective fitness evaluation function is adopted in the evolutionary algorithm. The multi-objective evaluation function is designed so that it allows incorporating complex linguistic features that a human observer would desire in the behaviors of the mobile robot movements. To illustrate the effectiveness of the proposed method, simulation results are compared using a conventional evolutionary algorithm.
AB - This paper presents an approach for evolving optimum behaviors for a nonholonomic mobile robot in a class of dynamic environments. A new evolutionary algorithm reflecting some powerful features in the natural evolutionary process to have flexibility to deal with changes in the environment is used to evolve optimum behaviors. Furthermore, a fuzzy set based multi-objective fitness evaluation function is adopted in the evolutionary algorithm. The multi-objective evaluation function is designed so that it allows incorporating complex linguistic features that a human observer would desire in the behaviors of the mobile robot movements. To illustrate the effectiveness of the proposed method, simulation results are compared using a conventional evolutionary algorithm.
KW - Dynamic environments
KW - Evolutionary algorithms
KW - Fuzzy behavior based control
KW - Fuzzy set based objective functions
KW - Nonholonomic mobile robot
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U2 - 10.1023/A:1013939308620
DO - 10.1023/A:1013939308620
M3 - Article
AN - SCOPUS:0035520705
VL - 32
SP - 255
EP - 277
JO - Journal of Intelligent and Robotic Systems: Theory and Applications
JF - Journal of Intelligent and Robotic Systems: Theory and Applications
SN - 0921-0296
IS - 3
ER -