Autonomous Robotics Self-Localization Using Genetic Algorithms

Author

Gutierrez, F. ; Atkinson, J.

Author_Institution

Dept. of Comput. Sci., Univ. de Concepcion, Concepcion, Chile

fYear

2009

fDate

2-4 Nov. 2009

Firstpage

167

Lastpage

170

Abstract

In this work, a new approach for robotics self-location using constrained genetic algorithms is proposed. The model uses a location estimation stage based on Kalman filters so as to redefine the search space and finds the most accurate current position of a robot. Experiments show the promise of the method to predict for robotic applications.

Keywords

Kalman filters; genetic algorithms; mobile robots; Kalman filters; autonomous robotics self-localization; constrained genetic algorithms; location estimation; Artificial intelligence; Filtering; Genetic algorithms; Intelligent robots; Motion measurement; Navigation; Orbital robotics; Performance evaluation; Robot sensing systems; Space technology; Autonomous robotics; genetic algorithms; self-location;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence, 2009. ICTAI '09. 21st International Conference on

Conference_Location

Newark, NJ

ISSN

1082-3409

Print_ISBN

978-1-4244-5619-2

Type

conf

DOI

10.1109/ICTAI.2009.30

Filename

5364326

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2834294