Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/3819
Título: A fuzzified systematic adjustment of the robotic Darwinian PSO
Autor: Couceiro, Micael S.
Machado, J. A. Tenreiro
Rocha, Rui P.
Ferreira, Nuno M. F.
Palavras-chave: Foraging
Swarm robotics
Parameter adjustment
Fuzzy logic
Context-based information
Adaptive behavior
Data: 2012
Editora: Elsevier
Relatório da Série N.º: Robotics and Autonomous Systems; Vol. 60, Issue 12
Resumo: The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization using natural selection to enhance the ability to escape from sub-optimal solutions. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots, hence decreasing the amount of required information exchange among robots. This paper further extends the previously proposed algorithm adapting the behavior of robots based on a set of context-based evaluation metrics. Those metrics are then used as inputs of a fuzzy system so as to systematically adjust the RDPSO parameters (i.e., outputs of the fuzzy system), thus improving its convergence rate, susceptibility to obstacles and communication constraints. The adapted RDPSO is evaluated in groups of physical robots, being further explored using larger populations of simulated mobile robots within a larger scenario.
Peer review: yes
URI: http://hdl.handle.net/10400.22/3819
ISSN: 0921-8890
Versão do Editor: http://www.sciencedirect.com/science/article/pii/S0921889012001753
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