{"id":4734,"date":"2023-08-27T20:53:35","date_gmt":"2023-08-27T20:53:35","guid":{"rendered":"https:\/\/dailyai.com\/?p=4734"},"modified":"2023-08-27T21:10:25","modified_gmt":"2023-08-27T21:10:25","slug":"mit-researchers-develop-technique-to-enhance-robotic-object-manipulation","status":"publish","type":"post","link":"https:\/\/dailyai.com\/es\/2023\/08\/mit-researchers-develop-technique-to-enhance-robotic-object-manipulation\/","title":{"rendered":"Investigadores del MIT desarrollan una t\u00e9cnica para mejorar la manipulaci\u00f3n rob\u00f3tica de objetos"},"content":{"rendered":"<p><b>Investigadores del Instituto Tecnol\u00f3gico de Massachusetts (MIT) han desarrollado una t\u00e9cnica de IA dise\u00f1ada para que los robots puedan manipular objetos utilizando todo su cuerpo.\u00a0<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Manipular objetos utilizando m\u00faltiples puntos de contacto en varias partes del cuerpo supone un enorme reto para los robots. Los humanos destacan en la manipulaci\u00f3n de todo el cuerpo, transportando sin problemas cajas grandes o sujetando objetos irregulares.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Sin embargo, los robots son mucho menos competentes en tareas de manipulaci\u00f3n complejas debido a los numerosos puntos de contacto entre los objetos y distintas partes de su cuerpo.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\"En lugar de pensar en esto como un sistema de 'caja negra', si podemos aprovechar la estructura de este tipo de sistemas rob\u00f3ticos utilizando modelos, existe la oportunidad de acelerar todo el procedimiento de intentar tomar estas decisiones e idear planes ricos en contactos\", afirma H.J. Terry Suh, estudiante de posgrado de Ingenier\u00eda El\u00e9ctrica e Inform\u00e1tica (EECS) y coautor principal del trabajo de investigaci\u00f3n.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">En esencia, el trabajo de los investigadores del MIT aborda la intensidad y complejidad computacional de las tareas de manipulaci\u00f3n rob\u00f3tica, concretamente las que implican escenarios ricos en contactos. A la hora de planificar una tarea de manipulaci\u00f3n, los robots deben tener en cuenta innumerables posibilidades de contacto con un objeto, lo que da lugar a un n\u00famero inabarcable de c\u00e1lculos.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Tradicionalmente, se han utilizado m\u00e9todos de aprendizaje por refuerzo (RL) para resolver este problema, pero requieren muchos recursos inform\u00e1ticos y mucho tiempo.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">En <a href=\"https:\/\/ieeexplore.ieee.org\/document\/10225433\">estudiar<\/a> introdujo el \"suavizado\" para resolver este problema. El proceso de \"suavizado\" agiliza la carga computacional reduciendo el n\u00famero de contactos que el robot debe tener en cuenta. Condensa la mir\u00edada de posibles puntos de contacto en un conjunto manejable de decisiones clave.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Esencialmente, muchas acciones y contactos intrascendentes que el robot podr\u00eda hacer se promedian, dejando s\u00f3lo los puntos vitales de interacci\u00f3n que necesitan ser calculados.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Para aplicar el \"suavizado\", el equipo dise\u00f1\u00f3 un modelo basado en la f\u00edsica.\u00a0<\/span><span style=\"font-weight: 400;\">Este modelo reproduce eficazmente el tipo de \"promediaci\u00f3n\" de las interacciones no cr\u00edticas que se produce impl\u00edcitamente en los m\u00e9todos de aprendizaje por refuerzo. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">El equipo prob\u00f3 su m\u00e9todo tanto en simulaciones como en hardware rob\u00f3tico del mundo real, mostrando un rendimiento comparable al del aprendizaje por refuerzo, pero a una fracci\u00f3n del coste computacional.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Aplicaciones pr\u00e1cticas<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Las implicaciones de esta investigaci\u00f3n pueden ser de gran alcance. En el \u00e1mbito industrial, la t\u00e9cnica podr\u00eda permitir la utilizaci\u00f3n de robots m\u00e1s peque\u00f1os y m\u00f3viles, capaces de realizar tareas complejas con mayor flexibilidad.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Esto podr\u00eda reducir tanto el consumo de energ\u00eda como los costes operativos. M\u00e1s all\u00e1 de las f\u00e1bricas, la tecnolog\u00eda podr\u00eda cambiar las reglas del juego de las misiones de exploraci\u00f3n espacial, permitiendo a los robots adaptarse r\u00e1pidamente a terrenos o tareas impredecibles con recursos computacionales m\u00ednimos.<\/span><\/p>\n<p>Adem\u00e1s, estos m\u00e9todos computacionales podr\u00edan ayudar a los investigadores a construir manos competentes y realistas.<\/p>\n<p><span style=\"font-weight: 400;\">\"Las mismas ideas que permiten la manipulaci\u00f3n de todo el cuerpo tambi\u00e9n sirven para planificar con manos diestras similares a las humanas\", afirma Russ Tedrake, autor principal y catedr\u00e1tico Toyota de EECS en el MIT.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Aunque la IA est\u00e1 impulsando transformaciones en el campo de la rob\u00f3tica, dotando a los robots de habilidades y conocimientos cada vez mejores, a\u00fan no hemos construido nada con destreza biol\u00f3gica. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">A medida que el hardware de IA se reduce <a href=\"https:\/\/dailyai.com\/es\/2023\/08\/ex-google-researchers-establish-an-innovative-bio-inspired-ai-startup\/\">chips de bajo consumo<\/a> y los investigadores encuentren formas de resolver los problemas computacionales, es probable que los robots diestros y con apariencia de vida no est\u00e9n muy lejos.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"<p>Investigadores del Instituto Tecnol\u00f3gico de Massachusetts (MIT) han desarrollado una t\u00e9cnica de inteligencia artificial dise\u00f1ada para que los robots puedan manipular objetos utilizando todo su cuerpo.  Manipular objetos utilizando m\u00faltiples puntos de contacto en varias partes del cuerpo supone un enorme reto para los robots. Los humanos destacan en la manipulaci\u00f3n de todo el cuerpo, transportando sin problemas cajas grandes o sujetando objetos irregulares.  Sin embargo, los robots son mucho menos competentes en tareas de manipulaci\u00f3n complejas debido a los numerosos puntos de contacto entre los objetos y distintas partes de su cuerpo.  \"En lugar de pensar en esto como un sistema de 'caja negra', si podemos aprovechar la estructura de este tipo de sistemas rob\u00f3ticos utilizando<\/p>","protected":false},"author":2,"featured_media":4735,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[105,117,169,130],"class_list":["post-4734","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-machine-learning","tag-mit","tag-robotics","tag-robots"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>MIT researchers develop technique to enhance robotic object manipulation | DailyAI<\/title>\n<meta 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