Collective Robotic Search Using Hybrid Techniques: Fuzzy Logic and Swarm Intelligence Inspired by Nature
This paper presents two new strategies for navigation of a swarm of robots for target/mission focused applications including landmine detection and firefighting. The first method presents an embedded fuzzy logic approach in the particle swarm optimization (PSO) algorithm robots and the second method presents a swarm of fuzzy logic controllers, one on each robot. The framework of both strategies has been inspired by natural swarms such as the school of fish or the flock of birds. In addition to the target search using the above methods, a hierarchy for the coordination of a swarm of robots has been proposed. The robustness of both strategies is evaluated for failures or loss in swarm members. Results are presented with both strategies and comparisons of their performance are carried out against a greedy search algorithm.
G. K. Venayagamoorthy et al., "Collective Robotic Search Using Hybrid Techniques: Fuzzy Logic and Swarm Intelligence Inspired by Nature," Engineering Applications of Artificial Intelligence, Elsevier, Apr 2009.
The definitive version is available at https://doi.org/10.1016/j.engappai.2008.10.002
Electrical and Computer Engineering
National Science Foundation (U.S.)
University of Missouri Research Board
Keywords and Phrases
Collective Robotic Search; Fuzzy Swarm; Greedy Search; Particle Swarm Optimization; Swarm Fuzzy; Fuzzy logic; Swarm intelligence
Article - Journal
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