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Robots que pueden adaptarse como animales.

Antoine Cully1, Jeff Clune2, Danesh Tarapore1

  • 11] Sorbonne Universités, Université Pierre et Marie Curie (UPMC), Paris 06, UMR 7222, Institut des Systèmes Intelligents et de Robotique (ISIR), F-75005, Paris, France [2] CNRS, UMR 7222, Institut des Systèmes Intelligents et de Robotique (ISIR), F-75005, Paris, France.

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Este estudio introduce un algoritmo inteligente de prueba y error que permite a los robots adaptarse rápidamente a los daños. Este avance permite a los robots aprender rápidamente comportamientos compensatorios, mejorando su robustez y autonomía en entornos complejos.

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Área de la Ciencia:

  • Robótica y Robótica Robótica y Robótica Robótica Robótica Robótica Robótica Robótica Robótica
  • La inteligencia artificial es inteligencia artificial.
  • Aprendizaje automático Aprendizaje automático.

Sus antecedentes:

  • Los robots ofrecen beneficios sociales significativos, pero están limitados por la fragilidad en entornos complejos.
  • Los robots actuales carecen de capacidades adaptativas para compensar el daño, a diferencia de los organismos biológicos.
  • Los métodos existentes de adaptación de daños para robots a menudo son lentos y requieren una extensa pre-programación.

Objetivo del estudio:

  • Desarrollar un algoritmo inteligente para una rápida adaptación al daño de los robots.
  • Permitir que los robots aprendan comportamientos compensatorios sin autodiagnóstico o planes predefinidos.
  • Para reducir la fragilidad de los robots y mejorar su autonomía en situaciones impredecibles.

Principales métodos:

  • Una técnica novedosa crea un mapa detallado de los comportamientos de robots de alto rendimiento antes de su despliegue.
  • Un algoritmo inteligente de aprendizaje por prueba y error utiliza este conocimiento previo para guiar la adaptación.
  • El algoritmo realiza experimentos rápidos e inteligentes para descubrir comportamientos de compensación de daños.

Principales resultados:

  • Robots adaptados a diversas lesiones en menos de dos minutos dentro de grandes espacios de búsqueda.
  • Se demostraron adaptaciones exitosas en un robot con piernas con múltiples lesiones en las piernas.
  • Un brazo robótico con numerosas fallas en las articulaciones también mostró una adaptación exitosa.

Conclusiones:

  • El nuevo algoritmo mejora significativamente la robustez del robot y la capacidad de adaptación al daño.
  • Este enfoque permite robots autónomos más eficaces para diversas aplicaciones.
  • Los hallazgos pueden ofrecer información sobre los principios biológicos de la adaptación a la lesión.