Title
Using Genetic Algorithms To Evolve The Control Rules Of A Swarm Of Uavs
Keywords
Behavior-based robots; Genetic algorithms; Swarming; UAV
Abstract
Due to the large number of interactions that the agents in a swarm of UAVs have with each other as well as with their environment, it is necessary to obtain a viable procedure that yields a reasonable group behavior from these local interactions. This paper proposes a hierarchical behavior-based model in which several parameters are adjusted with a genetic algorithm (GA). The presented model implements three explicit layers of behaviors (basic, group and mission) in a simulation in which the agents seek to survey a rectangular target area while avoiding a circular obstacle. © 2005 IEEE.
Publication Date
12-1-2005
Publication Title
Proceedings - 2005 International Symposium on Collaborative Technologies and Systems
Volume
2005
Number of Pages
359-365
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ISCST.2005.1553335
Copyright Status
Unknown
Socpus ID
33845475633 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/33845475633
STARS Citation
Soto, Jaime and Lin, Kuo Chi, "Using Genetic Algorithms To Evolve The Control Rules Of A Swarm Of Uavs" (2005). Scopus Export 2000s. 3249.
https://stars.library.ucf.edu/scopus2000/3249