{"id":226077,"date":"2025-11-28T13:10:45","date_gmt":"2025-11-28T19:10:45","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/11\/robots-combine-ai-learning-and-control-theory-to-perform-advanced-movements"},"modified":"2025-11-28T13:10:45","modified_gmt":"2025-11-28T19:10:45","slug":"robots-combine-ai-learning-and-control-theory-to-perform-advanced-movements","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/11\/robots-combine-ai-learning-and-control-theory-to-perform-advanced-movements","title":{"rendered":"Robots combine AI learning and control theory to perform advanced movements"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/robots-combine-ai-learning-and-control-theory-to-perform-advanced-movements2.jpg\"><\/a><\/p>\n<p>When it comes to training robots to perform agile, single-task motor skills, such as handstands or backflips, artificial intelligence methods can be very useful. But if you want to train your robot to perform multiple tasks\u2014say, performing a backward flip into a handstand\u2014things get a little more complicated.<\/p>\n<p>\u201cWe often want to train our robots to learn new skills by compounding existing skills with one another,\u201d said Ian Abraham, assistant professor of mechanical engineering. \u201cUnfortunately, AI models trained to allow robots to perform complex skills across many tasks tend to have worse performance than training on an individual task.\u201d<\/p>\n<p>To solve for that, Abraham\u2019s lab is using techniques from optimal control\u2014that is, taking a mathematical approach to help robots perform movements in the most efficient and optimal way possible. In particular, they\u2019re employing <a href=\"https:\/\/techxplore.com\/news\/2023-07-machine-learning-technique-efficiently-robot.html?utm_source=embeddings&utm_medium=related&utm_campaign=internal\" rel=\"related\">hybrid control theory<\/a>, which involves deciding when an autonomous system should switch between control modes to solve a task. The research is <a href=\"https:\/\/arxiv.org\/abs\/2510.19074\" target=\"_blank\">published<\/a> on the <i>arXiv<\/i> preprint server.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When it comes to training robots to perform agile, single-task motor skills, such as handstands or backflips, artificial intelligence methods can be very useful. But if you want to train your robot to perform multiple tasks\u2014say, performing a backward flip into a handstand\u2014things get a little more complicated. \u201cWe often want to train our robots [\u2026]<\/p>\n","protected":false},"author":662,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2229,6],"tags":[],"class_list":["post-226077","post","type-post","status-publish","format-standard","hentry","category-mathematics","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/226077","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/662"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=226077"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/226077\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=226077"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=226077"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=226077"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}