Darwinian Robotic Swarms for exploration with minimal communication

作者: Micael S Couceiro , Rui P Rocha , Nuno MF Ferreira , Patricia A Vargas , None

DOI: 10.1109/CEC.2013.6557562

关键词: Swarm roboticsArtificial intelligenceEvolutionary computationEvolutionary algorithmComputer scienceCommunication complexityRobotOverhead (computing)Population

摘要: The Robotic Darwinian Particle Swarm Optimization (RDPSO) recently introduced in the literature has ability to dynamically partition whole population of robots based on simple “punish-reward” rules. Although this evolutionary algorithm enables reduction amount required information exchange among robots, a further analysis communication complexity RDPSO needs be carried out so as evaluate its scalability. This paper analyses architecture system, thus describing dynamics data packet structure shared between teammates. Moreover, set rules is also proposed order reduce overhead within swarms robots. Experimental results with teams 15 real show that methodology reduces overhead, improving scalability and applicability algorithm.

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