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Controle Inteligente do Caminhar de Robôs Móveis Simulados

Controle Inteligente do Caminhar de Robôs Móveis Simulados

Controle Inteligente do Caminhar de Robôs Móveis Simulados

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9Figura 6. Robôs treina<strong>do</strong>s para transpor <strong>de</strong>sníveis e escadas<strong>de</strong> uma re<strong>de</strong> neural) através <strong>de</strong> robôs simula<strong>do</strong>s em um ambiente virtual realista.Além disso, o protótipo <strong>do</strong> mo<strong>de</strong>lo proposto permite a evolução da morfologia <strong>do</strong>robô em conjunto com os parâmetros <strong>de</strong> controle. Os resulta<strong>do</strong>s obti<strong>do</strong>s <strong>de</strong>monstramque: (i) as re<strong>de</strong>s neurais são bastante ecientes no controle das juntas<strong>do</strong> robô; (ii) o uso <strong>de</strong> algoritmos genéticos para a evolução <strong>do</strong>s pesos sinápticossurge como uma alternativa bastante atrativa <strong>de</strong> se resolver o problema da falta<strong>de</strong> informações locais para o cálculo <strong>do</strong> gradiente; (iii) a evolução da morfologiapermite que sejam <strong>de</strong>scobertos mo<strong>de</strong>los <strong>de</strong> robôs bastante ecientes.Agra<strong>de</strong>cimentosAgra<strong>de</strong>cemos ao apoio da CAPES e <strong>do</strong> CNPq a este traballho.Referências1. Heinen, M.R.: <strong>Controle</strong> inteligente <strong>do</strong> caminhar <strong>de</strong> robôs móveis simula<strong>do</strong>s.Dissertação <strong>de</strong> mestra<strong>do</strong>, Universida<strong>de</strong> <strong>do</strong> Vale <strong>do</strong> Rio <strong>do</strong>s Sinos (UNISI-NOS), São Leopol<strong>do</strong>, RS, Brasil (2007) Data <strong>de</strong> Conclusão: 20/02/2007. URL:http://bdtd.unisinos.br/t<strong>de</strong>_busca/arquivo.php?codArquivo=380.2. Knight, R., Nehmzow, U.: Walking robots - a survey and a research proposal.Technical Report CSM-375, Univ. Essex, Essex, UK (2002)3. Bekey, G.A.: Autonomous Robots: From Biological Inspiration to Implementationand Control. MIT Press, Cambridge, MA (2005)4. Pfeifer, R., Scheier, C.: Un<strong>de</strong>rstanding Intelligence. MIT Press, Cambridge, MA(1999)5. Chernova, S., Veloso, M.: An evolutionary approach to gait learning for four-leggedrobots. In: Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS),Sendai, Japan (2004)6. Mitchell, T.: Machine Learning. McGrall-Hill, New York (1997)7. Heinen, M.R., Osório, F.S.: Applying genetic algorithms to control gait of physicallybased simulated robots. In: Proc. IEEE Congr. Evolutionary Computation(CEC), Vancouver, Canada (2006)8. Heinen, M.R., Osório, F.S.: Applying genetic algorithms to control gait of simulatedrobots. In: Proc. IEEE Electronics, Robotics and Automotive Mechanics Conf.(CERMA) 2007, Cuernavaca, Morelos, Mexico (2007) 5005059. Heinen, M.R., Osório, F.S.: Gait control generation for physically based simulatedrobots using genetic algorithms. In: Proc. Int. Joint Conf. 2006, 10thIbero-American Conference on AI (IBERAMIA), 18th Brazilian Symposium onAI (SBIA). LNCS, Ribeirão Preto - SP, Brazil, Springer-Verlag (2006)

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