{"id":28143,"date":"2024-07-01T11:15:19","date_gmt":"2024-07-01T09:15:19","guid":{"rendered":"https:\/\/www.m-q.ch\/?p=19977"},"modified":"2024-11-10T08:37:08","modified_gmt":"2024-11-10T07:37:08","slug":"so-koennen-sich-roboter-energieeffizient-orientieren","status":"publish","type":"post","link":"https:\/\/www.organisator.ch\/fr\/operational-excellence\/2024-07-01\/so-koennen-sich-roboter-energieeffizient-orientieren\/","title":{"rendered":"Les robots peuvent ainsi s'orienter de mani\u00e8re efficace sur le plan \u00e9nerg\u00e9tique"},"content":{"rendered":"<figure id=\"attachment_19979\" class=\"wp-caption alignnone\" style=\"width: 680px\" aria-describedby=\"caption-attachment-19979\"><img class=\"alignnone wp-image-19979 size-full\" src=\"https:\/\/www.m-q.ch\/wp-content\/uploads\/2024\/07\/ZHAW_Bild1_ps.jpg\" alt=\"Odom\u00e9trie visuelle \" width=\"680\" height=\"458\" \/>\r\n<figcaption id=\"caption-attachment-19979\" class=\"wp-caption-text\">(Image : ZHAW - LSFM)<\/figcaption>\r\n<\/figure>\r\n<p>M\u00eame les petits animaux comme les abeilles, qui disposent de moins d'un million de neurones, peuvent facilement s'orienter dans des environnements complexes. Pour ce faire, ils utilisent des signaux visuels pour \u00e9valuer leurs propres mouvements et suivre leur position par rapport \u00e0 des lieux importants. Cette capacit\u00e9 est appel\u00e9e odom\u00e9trie visuelle. En termes de compacit\u00e9 et d'efficacit\u00e9 \u00e9nerg\u00e9tique, la solution utilis\u00e9e par les animaux est in\u00e9gal\u00e9e par rapport aux meilleures solutions techniques actuelles pour les robots. Mais pour que de nouvelles applications telles que les petits drones autonomes ou les lunettes l\u00e9g\u00e8res de r\u00e9alit\u00e9 augment\u00e9e deviennent possibles, l'efficacit\u00e9 \u00e9nerg\u00e9tique doit \u00eatre massivement am\u00e9lior\u00e9e.\u00a0<\/p>\r\n<figure id=\"attachment_19980\" class=\"wp-caption alignnone\" style=\"width: 680px\" aria-describedby=\"caption-attachment-19980\"><img class=\"size-full wp-image-19980\" src=\"https:\/\/www.m-q.ch\/wp-content\/uploads\/2024\/07\/ZHAW_Bild2_ps.jpg\" alt=\"\" width=\"680\" height=\"283\" \/>\r\n<figcaption id=\"caption-attachment-19980\" class=\"wp-caption-text\">Une cam\u00e9ra neuromorphique bas\u00e9e sur les \u00e9v\u00e9nements a \u00e9t\u00e9 mont\u00e9e sur le bras du robot. Tout comme notre \u0153il, elle enregistre les changements dans la sc\u00e8ne sous forme d'\"\u00e9v\u00e9nements\". Ceux-ci sont encod\u00e9s avec des vecteurs d'activation et envoy\u00e9s \u00e0 un r\u00e9sonateur neuronal. L\u00e0, une m\u00e9moire \u00e0 court terme de la sc\u00e8ne visuelle est cr\u00e9\u00e9e, les objets de la sc\u00e8ne sont suivis et le mouvement de la cam\u00e9ra est calcul\u00e9. Le syst\u00e8me g\u00e9n\u00e8re ainsi une repr\u00e9sentation qui est transparente, c'est-\u00e0-dire compr\u00e9hensible par un \u00eatre humain et pertinente pour la t\u00e2che. (Image : Nature Machine Intelligence)<\/figcaption>\r\n<\/figure>\r\n<h3><strong>Construit selon l'exemple des r\u00e9seaux neuronaux naturels<\/strong><\/h3>\r\n<p>Dans ces travaux, publi\u00e9s dans Nature Machine Intelligence, une \u00e9quipe internationale d'auteurs propose une nouvelle solution neuromorphique, c'est-\u00e0-dire construite sur le mod\u00e8le des r\u00e9seaux neuronaux naturels, qui peut \u00e9galement \u00eatre impl\u00e9ment\u00e9e efficacement dans du mat\u00e9riel neuromorphique. Les r\u00e9sultats pr\u00e9sent\u00e9s constituent une \u00e9tape importante vers l'utilisation de mat\u00e9riel informatique neuromorphique pour l'odom\u00e9trie visuelle rapide et peu gourmande en \u00e9nergie, ainsi que pour la t\u00e2che de localisation et de cartographie simultan\u00e9es qui en d\u00e9coule. Les chercheurs ont valid\u00e9 exp\u00e9rimentalement cette approche dans une t\u00e2che robotique simple et ont pu montrer, \u00e0 l'aide d'un ensemble de donn\u00e9es bas\u00e9es sur des \u00e9v\u00e9nements, que la performance correspond \u00e0 l'\u00e9tat de l'art dans ce domaine.<\/p>\r\n<h3><strong>Plus de transparence dans l'IA <\/strong><\/h3>\r\n<p>La grande diff\u00e9rence avec l'IA actuelle, telle qu'elle est utilis\u00e9e par exemple par ChatGTP, r\u00e9side dans le fait que la m\u00e9thode d\u00e9crite peut assembler ou d\u00e9sassembler diff\u00e9rents composants d'une sc\u00e8ne visuelle en une composition. Ces composants sont des informations telles que \"Quels objets s'y trouvent ?\" ou \"O\u00f9 se trouvent-ils ?\" et bien d'autres encore. Dans les r\u00e9seaux neuronaux conventionnels, ces composants sont m\u00e9lang\u00e9s et ne peuvent pas \u00eatre d\u00e9m\u00eal\u00e9s. La nouvelle m\u00e9thode le peut. Ceci est d'une importance capitale pour d\u00e9velopper des syst\u00e8mes d'IA modulaires et surtout \u00e9galement transparents.\u00a0<\/p>\r\n<p><a href=\"https:\/\/www.zhaw.ch\/de\/lsfm\/\"><em>Source : ZHAW - LSFM \u00a0<\/em><\/a><\/p>\n<p class=\"syndicated-attribution\">Cet article est paru initialement sur m-q.ch - <a href=\"https:\/\/www.m-q.ch\/de\/so-koennen-sich-roboter-energieeffizient-orientieren\/\" target=\"_blank\">https:\/\/www.m-q.ch\/de\/so-koennen-sich-roboter-energieeffizient-orientieren\/<\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>Pour que les robots puissent se d\u00e9placer de mani\u00e8re autonome dans l'espace, ils doivent pouvoir estimer o\u00f9 ils se trouvent et comment ils se d\u00e9placent. Jusqu'\u00e0 pr\u00e9sent, cela n'\u00e9tait possible qu'au prix de gros efforts de calcul et d'une grande consommation d'\u00e9nergie. Une \u00e9quipe de recherche, \u00e0 laquelle participe la chercheuse de la ZHAW Yulia Sandamirskaya, a d\u00e9velopp\u00e9 une nouvelle solution peu gourmande en \u00e9nergie et d\u00e9montr\u00e9 son applicabilit\u00e9 \u00e0 une t\u00e2che robotique r\u00e9elle. Les r\u00e9sultats ont \u00e9t\u00e9 publi\u00e9s dans la c\u00e9l\u00e8bre revue sp\u00e9cialis\u00e9e Nature Machine Intelligence.<\/p>","protected":false},"author":58,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_yoast_wpseo_focuskw":"Visuelle Odometrie","_yoast_wpseo_metadesc":"Visuelle Odometrie: Neuromorphe Kameras verbessern Energieeffizienz und Transparenz in autonomen Systemen und Augmented Reality.","articlekey":"","footnotes":""},"categories":[582],"tags":[218,298,605,2600],"class_list":["post-28143","post","type-post","status-publish","format-standard","hentry","category-operational-excellence","tag-forschung","tag-ki","tag-qualitaetsmanagement","tag-zhaw"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>So k\u00f6nnen sich Roboter energieeffizient orientieren - Organisator<\/title>\n<meta name=\"description\" content=\"Visuelle Odometrie: Neuromorphe Kameras verbessern Energieeffizienz und Transparenz in autonomen Systemen und Augmented Reality.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.organisator.ch\/fr\/excellence-operationnelle\/2024-07-01\/so-koennen-sich-roboter-energieeffizient-orientieren\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"So k\u00f6nnen sich Roboter energieeffizient orientieren - 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