Details
| Original language | English |
|---|---|
| Title of host publication | MICAI 2006 |
| Subtitle of host publication | Advances in Artificial Intelligence - 5th Mexican International Conference on Artificial Intelligence, Proceedings |
| Publisher | Springer Verlag |
| Pages | 101-111 |
| Number of pages | 11 |
| ISBN (print) | 3540490264, 9783540490265 |
| Publication status | Published - 2006 |
| Externally published | Yes |
| Event | 5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence - Apizaco, Mexico Duration: 13 Nov 2006 → 17 Nov 2006 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 4293 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
In this paper we investigate real-time adaptive extensions of our fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. The main idea is to introduce active battery level sensors und recharge zones to improve robot behavior for reaching survivability in environment exploration. In order to achieve this goal, we propose an improvement of our previously defined model, as well as a hybrid controller for a mobile robot, combining behavior-based and mission-oriented control mechanism. This method is implemented and tested in action sequence based environment exploration tasks in a Khepera mobile robot simulator. We investigate our technique with several sets of configuration parameters and scenarios. The experiments show a significant improvement in robot responsiveness regarding survivability and environment exploration.
Keywords
- Environment exploration, Fuzzy logic, Mobile robot, Real-time
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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MICAI 2006: Advances in Artificial Intelligence - 5th Mexican International Conference on Artificial Intelligence, Proceedings. Springer Verlag, 2006. p. 101-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4293 LNAI).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Real-time adaptive fuzzy motivations for evolutionary behavior learning by a mobile robot
AU - Freund, Wolfgang
AU - Vidal, Tomas Arredondo
AU - Muñoz, César
AU - Navarro, Nicolás
AU - Quirós, Fernando
PY - 2006
Y1 - 2006
N2 - In this paper we investigate real-time adaptive extensions of our fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. The main idea is to introduce active battery level sensors und recharge zones to improve robot behavior for reaching survivability in environment exploration. In order to achieve this goal, we propose an improvement of our previously defined model, as well as a hybrid controller for a mobile robot, combining behavior-based and mission-oriented control mechanism. This method is implemented and tested in action sequence based environment exploration tasks in a Khepera mobile robot simulator. We investigate our technique with several sets of configuration parameters and scenarios. The experiments show a significant improvement in robot responsiveness regarding survivability and environment exploration.
AB - In this paper we investigate real-time adaptive extensions of our fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. The main idea is to introduce active battery level sensors und recharge zones to improve robot behavior for reaching survivability in environment exploration. In order to achieve this goal, we propose an improvement of our previously defined model, as well as a hybrid controller for a mobile robot, combining behavior-based and mission-oriented control mechanism. This method is implemented and tested in action sequence based environment exploration tasks in a Khepera mobile robot simulator. We investigate our technique with several sets of configuration parameters and scenarios. The experiments show a significant improvement in robot responsiveness regarding survivability and environment exploration.
KW - Environment exploration
KW - Fuzzy logic
KW - Mobile robot
KW - Real-time
UR - http://www.scopus.com/inward/record.url?scp=33845950594&partnerID=8YFLogxK
U2 - 10.1007/11925231_10
DO - 10.1007/11925231_10
M3 - Conference contribution
AN - SCOPUS:33845950594
SN - 3540490264
SN - 9783540490265
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 101
EP - 111
BT - MICAI 2006
PB - Springer Verlag
T2 - 5th Mexican International Conference on Artificial Intelligence, MICAI 2006
Y2 - 13 November 2006 through 17 November 2006
ER -