Optimal PSO for Collective Robotic Search Applications
Abstract
Unmanned vehicles/mobile robots are of particular interest in target tracing applications since there are many areas where a human cannot explore. Different means of control have been investigated for unmanned vehicles with various algorithms like genetic algorithms, evolutionary computations, neural networks etc. This paper presents the application of Particle Swarm Optimization (PSO) for collective robotic search. the performance of the PSO algorithm depends on various parameters called quality factors and these parameters are determined using a secondary PSO. Results are presented to show that the performance of PSO algorithm and search is improved for a single and multiple target searches.
Recommended Citation
S. Doctor et al., "Optimal PSO for Collective Robotic Search Applications," Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004, vol. 2, pp. 1390 - 1395, Institute of Electrical and Electronics Engineers, Sep 2004.
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-078038515-3
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
13 Sep 2004
