Abstract
In this article we consider a version of the Particle Swarm Optimization (PSO) algorithm which is appropriate for search tasks of multi-agent systems consisting of small robots with limited sensing capability. The proposed method adopts asynchronous mechanism for information exchange and position (way point) updates of the agents. Moreover, at each (information exchange) step the agents communicate with only a possibly different subset of the other agents leading to a dynamic neighborhood topology. We implement the algorithm using the Player/Stage realistic robot simulator as well as on real KheperaIII robots using experimentally collected realistic data of ethanol gas concentration. Simulation and implementation results show that the algorithm performs well in a sense that the robots are able to move towards and aggregate in areas with high gas concentration around the maximum points of the gas concentration profile representing the environment.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Turkish Journal of Electrical Engineering and Computer Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
