Details
| Original language | English |
|---|---|
| Pages | 417-421 |
| Number of pages | 5 |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 5th Meeting of the Electronics, Robotics and Automotive Mechanics Conference 2008, CERMA 2008 - Cuernavaca, Morelos, Mexico Duration: 30 Sept 2008 → 3 Oct 2008 |
Conference
| Conference | 5th Meeting of the Electronics, Robotics and Automotive Mechanics Conference 2008, CERMA 2008 |
|---|---|
| Country/Territory | Mexico |
| City | Cuernavaca, Morelos |
| Period | 30 Sept 2008 → 3 Oct 2008 |
Abstract
This paper describes the use of softcomputing based techniques toward the acquisition of adaptive behaviors to be used in mobile exploration by cooperating robots. Navigation within unknown environments and the obtaining of dynamic behavior require some method of unsupervised learning given the impossibility of programming strategies to follow for each individual case and for every possible situation the robot may face [1,5]. In this investigation in particular, it is intended to expose some of the benefits of cooperative learning robots using novel biologically inspired heuristic methods. Experiments were conducted using a Khepera mobile robot simulator which uses a neural network to generate behaviors based on robot sensor measurements. The training of this network was carried out with a Genetic Algorithm, where each individual is a neural network whose fitness function is the output of a function, proportional to the area covered by the robot.
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
- Engineering(all)
- Automotive Engineering
- Engineering(all)
- Electrical and Electronic Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
2008. 417-421 Paper presented at 5th Meeting of the Electronics, Robotics and Automotive Mechanics Conference 2008, CERMA 2008, Cuernavaca, Morelos, Mexico.
Research output: Contribution to conference › Paper › Research › peer review
}
TY - CONF
T1 - Cooperative adaptive behavior acquisition in mobile robot swarms using neural networks and genetic algorithms
AU - Muñoz, Cesar
AU - Navarro, Nicolás
AU - Arredondo, Tomás
AU - Freund, Wolfgang
PY - 2008
Y1 - 2008
N2 - This paper describes the use of softcomputing based techniques toward the acquisition of adaptive behaviors to be used in mobile exploration by cooperating robots. Navigation within unknown environments and the obtaining of dynamic behavior require some method of unsupervised learning given the impossibility of programming strategies to follow for each individual case and for every possible situation the robot may face [1,5]. In this investigation in particular, it is intended to expose some of the benefits of cooperative learning robots using novel biologically inspired heuristic methods. Experiments were conducted using a Khepera mobile robot simulator which uses a neural network to generate behaviors based on robot sensor measurements. The training of this network was carried out with a Genetic Algorithm, where each individual is a neural network whose fitness function is the output of a function, proportional to the area covered by the robot.
AB - This paper describes the use of softcomputing based techniques toward the acquisition of adaptive behaviors to be used in mobile exploration by cooperating robots. Navigation within unknown environments and the obtaining of dynamic behavior require some method of unsupervised learning given the impossibility of programming strategies to follow for each individual case and for every possible situation the robot may face [1,5]. In this investigation in particular, it is intended to expose some of the benefits of cooperative learning robots using novel biologically inspired heuristic methods. Experiments were conducted using a Khepera mobile robot simulator which uses a neural network to generate behaviors based on robot sensor measurements. The training of this network was carried out with a Genetic Algorithm, where each individual is a neural network whose fitness function is the output of a function, proportional to the area covered by the robot.
UR - http://www.scopus.com/inward/record.url?scp=67650091052&partnerID=8YFLogxK
U2 - 10.1109/CERMA.2008.89
DO - 10.1109/CERMA.2008.89
M3 - Paper
AN - SCOPUS:67650091052
SP - 417
EP - 421
T2 - 5th Meeting of the Electronics, Robotics and Automotive Mechanics Conference 2008, CERMA 2008
Y2 - 30 September 2008 through 3 October 2008
ER -