{"id":5549,"date":"2024-03-15T09:18:58","date_gmt":"2024-03-15T01:18:58","guid":{"rendered":"https:\/\/www.1ai.net\/?p=5549"},"modified":"2024-03-15T09:18:58","modified_gmt":"2024-03-15T01:18:58","slug":"%e5%9b%9b%e8%b6%b3%e6%9c%ba%e5%99%a8%e4%ba%ba-anymal-%e8%a7%a3%e9%94%81%e6%96%b0%e6%8a%80%e8%83%bd%ef%bc%9a%e5%8f%af%e8%b7%91%e9%85%b7%ef%bc%8c%e5%ba%94%e5%af%b9%e5%b7%a5%e5%9c%b0%e3%80%81%e7%81%be","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/5549.html","title":{"rendered":"ANYmal, a quadruped robot, unlocks new skills: parkour, capable of handling complex terrains such as construction sites and disaster areas"},"content":{"rendered":"<p data-vmark=\"a0da\"><strong>Four-legged<a href=\"https:\/\/www.1ai.net\/en\/tag\/%e6%9c%ba%e5%99%a8%e4%ba%ba\" title=\"[Sees articles with [robots] labels]\" target=\"_blank\" >robot<\/a> <a href=\"https:\/\/www.1ai.net\/en\/tag\/anymal\" title=\"[See articles with [ANYmal] labels]\" target=\"_blank\" >ANYmal<\/a> Unlocking new skills. - Runnin'<\/strong>A research team from ETH Zurich has recently upgraded the quadruped robot ANYmal, allowing it to navigate complex urban environments, use its motor skills to successfully pass obstacles, and be able to expertly deal with complex terrain commonly seen on construction sites or in disaster areas.<\/p>\n<p data-vmark=\"2191\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-5550\" title=\"1cf824da-eac8-4e1e-a03c-ac8475fece7a\" src=\"https:\/\/www.1ai.net\/wp-content\/uploads\/2024\/03\/1cf824da-eac8-4e1e-a03c-ac8475fece7a.jpg\" alt=\"1cf824da-eac8-4e1e-a03c-ac8475fece7a\" width=\"800\" height=\"450\" \/><\/p>\n<p data-vmark=\"fc6f\">The team, led by Professor Marco Hutter of the Department of Mechanical and Process Engineering, combined machine learning with model-based control to upgrade the algorithm so that it can accurately identify and pass through gaps\/grooves in rubble, allowing it to flexibly traverse complex terrain.<\/p>\n<p data-vmark=\"6cca\">ANYmal can climb obstacles and perform dynamic maneuvers to jump off them. In the process, ANYmal learns through trial and error, just like a child. Now, when it encounters an obstacle, ANYmal uses a camera and an artificial neural network to determine what kind of obstacle it is facing. It then makes a move that is likely to succeed based on its previous training.<\/p>\n<p data-vmark=\"e9c8\">Professor Hutter said there is still a lot of room for improvement in the algorithm, including freeing the robot from being limited to solving predefined problems and requiring it to calculate its way through difficult terrain (such as disaster areas covered with rubble).<\/p>","protected":false},"excerpt":{"rendered":"<p>Four-foot robot ANYmal unlocks new skills - running cool. The scientific team from the Federal Polytechnic Institute of Zurich has recently upgraded four robots, ANYmal, to manage the city ' s complex environment, to use motor skills to successfully pass through barriers and to be skilled in the complex terrain that is common in construction sites or disaster areas. The team is led by Professor Marco Hutter of the Department of Mechanical and Technological Engineering, who, in conjunction with machine learning and model-based control, upgrades algorithms to allow it to identify and pass through the cracks\/docks in the rubble, so that it can travel through complex terrain with flexibility. ANYmal can climb the barrier and perform dynamic motions to jump off the barrier. In the process, ANYmal comes by trying and making mistakes like a child<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[1684,909],"collection":[],"class_list":["post-5549","post","type-post","status-publish","format-standard","hentry","category-news","tag-anymal","tag-909"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/5549","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=5549"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/5549\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=5549"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=5549"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=5549"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=5549"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}