Repositório do Conhecimento Institucional do Centro Universitário FEI
 

Engenharia de Robôs

URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/339

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Resultados da Pesquisa

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  • Artigo de evento 2 Citação(ões) na Scopus
    Humanoid robot gait on sloping floors using reinforcement learning
    (2016-01-05) SILVA, I. J.; PERICO, D. H.; HOMEM, T. P. D.; VILAO, C. O.; Reinaldo Bianchi; Flavio Tonidandel
    © Springer International Publishing AG 2016.Climbing ramps is an important ability for humanoid robots: ramps exist everywhere in the world, such as in accessibility ramps and building entrances. This works proposes the use of Reinforcement Learning to learn the action policy that will make a robot walk in an upright position, in a lightly sloped terrain. The proposed architecture of our system is a two-layer combination of the traditional gait generation control loop with a reinforcement learning component. This allows the use of an accelerometer to generate a correction for the gait, when the slope of the floor where the robot is walking changes. Experiments performed on a real robot showed that the proposed architecture is a good solution for the stability problem.