Swarm Intelligence for Collective Robotic Search
Abstract
This chapter presents three strategies for the navigation of a swarm of robots for a target search application in a hazardous environment. the strategies explored include greedy search and two computational intelligence techniques-particle swarm optimization and fuzzy logic. Results for the collective search are presented for simulated environments containing single and multiple targets, with and without obstacles. the proposed navigation strategies can be further developed and applied to real-world applications such as aiding in disaster recovery, detection of hazardous materials, and many other high-risk tasks. © 2009 Springer-Verlag Berlin Heidelberg.
Recommended Citation
L. L. Grant and G. K. Venayagamoorthy, "Swarm Intelligence for Collective Robotic Search," Studies in Computational Intelligence, vol. 177, pp. 29 - 47, Springer, Dec 2009.
The definitive version is available at https://doi.org/10.1007/978-3-540-89933-4_2
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-354089932-7
International Standard Serial Number (ISSN)
1860-949X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Dec 2009
