DocumentCode
2687661
Title
A fitness-sharing based genetic algorithm for collaborative Multi Robot Localization
Author
Bori, Francesco ; Gasparri, Andrea ; Panzieri, Stefano
Author_Institution
Dept. of Comput. Sci., Univ. of Roma Tre, Rome, Italy
fYear
2009
fDate
10-15 Oct. 2009
Firstpage
3968
Lastpage
3973
Abstract
In this paper, a novel genetic algorithm based on a ¿collaborative¿ fitness-sharing technique to deal with the Multi-Robot Localization problem is proposed. Indeed, the use of the fitness-sharing is twofold and competitive. It preserves the diversity among individuals during the space exploration process, thus maintaining evolutionary niches over time, and reinforces the best hypotheses by means of collaboration among robots, thus augmenting the selection pressure. Simulations by exploiting the robotics framework Player/Stage have been performed along with a proper statistical analysis for performance assessment.
Keywords
genetic algorithms; multi-robot systems; simulation; statistical analysis; collaborative multi robot localization; fitness-sharing; genetic algorithm; performance assessment; simulations; statistical analysis; Collaborative work; Genetic algorithms; Intelligent robots; International collaboration; Multirobot systems; Navigation; Orbital robotics; Robot localization; Robot sensing systems; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Conference_Location
St. Louis, MO
Print_ISBN
978-1-4244-3803-7
Electronic_ISBN
978-1-4244-3804-4
Type
conf
DOI
10.1109/IROS.2009.5354581
Filename
5354581
Link To Document