Formation Control Optimization for Odor Localization View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Bambang Tutuko , Siti Nurmaini , Rendyansyah , P. P. Aditya , Saparudin

ABSTRACT

This paper presents a swarm robots formation control by using a new hybrid algorithm Fuzzy-Kohonen Networks and Particle Swarm Optimization (FKN-PSO). The FKN-PSO approach is proposed, to overcome the formation control problem due to the loss of a source of odor, caused by the failure in sensor detection, fail in robot motion control and environmental uncertainty in odor localization. The experiments are conducted by using simple swarm robots in the real environment with on-board sensor and processor. The results are compared between FKN-PSO and Fuzzy-PSO to look at the performance of the swarm robots in the process of odor localization. As the results found that the propose algorithm produce fast response and efficiently process than Fuzzy-PSO, they are able to locate the source of odor in a short time and capable for keeping in formation to find the target. More... »

PAGES

51-61

References to SciGraph publications

Book

TITLE

Recent Advances on Soft Computing and Data Mining

ISBN

978-3-319-51279-2
978-3-319-51281-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-51281-5_6

DOI

http://dx.doi.org/10.1007/978-3-319-51281-5_6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019825242


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