{"id":4232,"date":"2022-12-20T00:21:52","date_gmt":"2022-12-19T21:21:52","guid":{"rendered":"http:\/\/www.artificialbrain.xyz\/?p=4232"},"modified":"2023-01-13T00:49:33","modified_gmt":"2023-01-12T21:49:33","slug":"underactuated-robotics-course-mit","status":"publish","type":"post","link":"https:\/\/www.newworldai.com\/underactuated-robotics-course-mit\/","title":{"rendered":"Underactuated Robotics Course  &#8211; MIT"},"content":{"rendered":"<h2 style=\"text-align: left;\"><em><strong><span style=\"font-family: helvetica, arial, sans-serif;\">Robots today move far too conservatively, and accomplish only a fraction of the tasks and achieve a fraction of the performance that they are mechanically capable of. <\/span><\/strong><\/em><\/h2>\n<p><span style=\"font-family: helvetica, arial, sans-serif;\">In many cases, we are still fundamentally limited by control technology which matured on rigid robotic arms in structured factory environments. The study of underactuated robotics focuses on building control systems which use the natural dynamics of the machines in an attempt to achieve extraordinary performance in terms of speed, efficiency, or robustness.<\/span><\/p>\n<h2 class=\"title style-scope ytd-video-primary-info-renderer\">\u00a0MIT 6.832 Underactuated Robotics, Spring 2009<\/h2>\n<p><span style=\"color: #ff0000;\"><strong>Instructor:<\/strong> <\/span>Russell Tedrake<\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 1 |Introduction<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/Z8oMbOj9IWM\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 2 | The Simple Pendulum<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/-RRYZ-b9NpI\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><span data-mce-type=\"bookmark\" style=\"display: inline-block; width: 0px; overflow: hidden; line-height: 0;\" class=\"mce_SELRES_start\">\ufeff<\/span><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 3 | Optimal control of the double integrator<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/oWr1_LybOZI\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 4 | Optimal control of the double integrator (continued)<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/89GQHKOeUcU\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 5 | Numerical optimal control (dynamic programming)<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/4kB94UDwJ0M\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 6 | Acrobot and cart-pole<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/QI09XKVW_8E\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 7 | Swing-up control of acrobot and cart-pole systems<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/9qnpQ1hVlqw\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 8 | Dynamic programming (DP) and policy search<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/Gho0bmTsnA4\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 9 | Trajectory optimization<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/g-VehRFsDcI\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 10 | Trajectory stabilization and iterative linear quadratic regulator (iLQR)<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/xwgIkdBQku4\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 11 | Walking<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/-fCLJ1pGht4\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 12 | Walking (continued)<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/E-sOMfDVe8o\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 13 | Running<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/CUygqWS7occ\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 14 | Feasible motion planning<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/ufM3HLTZ47k\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 15 | Global policies from local policies<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/7nnFGxqRwNE\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 16 | Introducing stochastic optimal control<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/KNRMz9YPCOY\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 17 | Stochastic Gradient Descent<\/strong><\/span><br \/>\n<span style=\"color: #800080;\"><strong> Instructor: John W. Roberts<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/6v3Ln2ACtqI\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 18 | Stochastic Gradient Descent 2<\/strong><\/span><br \/>\n<span style=\"color: #800080;\"><strong> Instructor: John W. Roberts<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/EqAYRo4wXxY\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 19 | Temporal difference learning<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/qtmmwILxVR4\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 20 | Temporal difference learning with function approximation<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/ja56bJ8ogUw\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 21: Policy improvement<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/7LLUz7A1--Q\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 22 | Actor-Critic methods<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/Bhbk4bWV1Uc\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><span style=\"color: #800080;\"><strong>Lecture 23 | Case studies in computational underactuated control<\/strong><\/span><\/p>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/7la43dvoLh0\" width=\"760\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><em><strong><a class=\"yt-simple-endpoint style-scope yt-formatted-string\" href=\"https:\/\/www.youtube.com\/channel\/UCEBb1b_L6zDS3xTUrIALZOw\">Source: MIT OpenCourseWare<\/a><\/strong><\/em><\/p>\n<p style=\"text-align: justify;\"><em>Russ Tedrake is a Full Professor in the Department of Electrical Engineering and Computer Science at MIT, and a member of the Computer Science and Artificial Intelligence Lab. He received his B.S.E. in Computer Engineering from the University of Michigan, Ann Arbor, in 1999, and his Ph.D. in Electrical Engineering and Computer Science from MIT in 2004, working with Sebastian Seung. After graduation, he spent a year with the MIT Brain and Cognitive Sciences Department as a Postdoctoral Associate. During his education, he has spent time at Microsoft, Microsoft Research, and the Santa Fe Institute.<\/em><\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"alignnone wp-image-4236\" src=\"http:\/\/www.artificialbrain.xyz\/wp-content\/uploads\/Russel-Tedrake-450x300.jpg\" alt=\"\" width=\"804\" height=\"536\" srcset=\"https:\/\/www.newworldai.com\/wp-content\/uploads\/Russel-Tedrake-450x300.jpg 450w, https:\/\/www.newworldai.com\/wp-content\/uploads\/Russel-Tedrake-150x100.jpg 150w, https:\/\/www.newworldai.com\/wp-content\/uploads\/Russel-Tedrake.jpg 560w\" sizes=\"(max-width: 804px) 100vw, 804px\" \/><\/p>\n<p style=\"text-align: justify;\"><em>Professor Tedrake&#8217;s research group is interested in underactuated motor control systems in animals and machines that are capable of executing dynamically dexterous tasks and interacting with uncertain environments. They believe that the design of these control systems is intimately related to the mechanical designs of their machines, and that tools from machine learning and optimal control can be used to exploit this coupling when classical control techniques fail. Current projects include robust and efficient bipedal locomotion on flat terrain, multi-legged locomotion over extreme terrain, flapping-winged flight, and feedback control for fluid dynamics.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Robots today move far too conservatively, and accomplish only a fraction of the tasks and achieve a fraction of the performance that they are<\/p>\n","protected":false},"author":2,"featured_media":4234,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1405],"tags":[1270,1269,1268],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.2.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Underactuated Robotics Course - MIT - New World : Artificial Intelligence<\/title>\n<meta name=\"description\" content=\"Robots today move far too conservatively, and accomplish only a fraction of the tasks and achieve a fraction of the performance.\" \/>\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.newworldai.com\/underactuated-robotics-course-mit\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Underactuated Robotics Course - MIT - New World : Artificial Intelligence\" \/>\n<meta property=\"og:description\" content=\"Robots today move far too conservatively, and accomplish only a fraction of the tasks and achieve a fraction of the performance.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.newworldai.com\/underactuated-robotics-course-mit\/\" \/>\n<meta property=\"og:site_name\" content=\"New World : Artificial Intelligence\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/groups\/952169468169594\/\" \/>\n<meta property=\"article:published_time\" content=\"2022-12-19T21:21:52+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-01-12T21:49:33+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.newworldai.com\/wp-content\/uploads\/underactuated-robotics.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"960\" \/>\n\t<meta property=\"og:image:height\" content=\"720\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"mussem\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@NewWorldAI1\" \/>\n<meta name=\"twitter:site\" content=\"@NewWorldAI1\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"mussem\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.newworldai.com\/underactuated-robotics-course-mit\/\",\"url\":\"https:\/\/www.newworldai.com\/underactuated-robotics-course-mit\/\",\"name\":\"Underactuated Robotics Course - MIT - New World : Artificial Intelligence\",\"isPartOf\":{\"@id\":\"https:\/\/www.newworldai.com\/#website\"},\"datePublished\":\"2022-12-19T21:21:52+00:00\",\"dateModified\":\"2023-01-12T21:49:33+00:00\",\"author\":{\"@id\":\"https:\/\/www.newworldai.com\/#\/schema\/person\/9d8dd21ba4efacdbf5a5a7700ac3ec1f\"},\"description\":\"Robots today move far too conservatively, and accomplish only a fraction of the tasks and achieve a fraction of the performance.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.newworldai.com\/underactuated-robotics-course-mit\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.newworldai.com\/underactuated-robotics-course-mit\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.newworldai.com\/underactuated-robotics-course-mit\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.newworldai.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Underactuated Robotics Course &#8211; 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