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Descripción
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| Motion generation is one of the most important and challenging problems in multi-legged robot research. Most of the existing methods show a good fulfillment of the requirements of robots in structured environments. However, it still faces many challenges to generate motions effectively and quickly for multi-legged robot works in complex environments. In this paper, we put forward a method which converts the motion generation problem into a Multi- objective Optimization Problem (MOP), which will make the robot not only run as fast as possible, but also save energy, and then use a distribution estimation algorithm, the trend prediction model method, to obtain motions for a six-legged robot. Experiments show that this method is effective. | |
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Internacional
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Si |
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Nombre congreso
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Symposium Series on Computational Intelligence 2017 |
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Tipo de participación
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960 |
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Lugar del congreso
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Revisores
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Si |
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ISBN o ISSN
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978-1-5386-2726-6 |
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DOI
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Fecha inicio congreso
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27/11/2017 |
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Fecha fin congreso
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01/12/2017 |
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Desde la página
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1 |
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Hasta la página
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6 |
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Título de las actas
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Computational Intelligence (SSCI), 2017 IEEE Symposium Series on |