{"id":2847,"date":"2018-07-18T03:24:04","date_gmt":"2018-07-18T03:24:04","guid":{"rendered":"http:\/\/brl.ee.washington.edu\/?page_id=2847"},"modified":"2018-07-18T03:24:04","modified_gmt":"2018-07-18T03:24:04","slug":"quantifying-hcps-interactions","status":"publish","type":"page","link":"https:\/\/wp.ece.uw.edu\/brl\/neural-engineering\/quantifying-hcps-interactions\/","title":{"rendered":"Quantifying HCPS interactions"},"content":{"rendered":"<h3>The Problem<\/h3>\n<p>Human interaction with the physical world is increasingly mediated by intelligent machines, such as surgical robots and active prostheses \/ orthoses. While machines can be engineered to produce a high degree of accuracy for a given input, current models of human-computer interaction, specifically how humans learn to operate these machines are still under investigation. Our\u00a0goal is\u00a0to amplify this interaction by designing machines that adapt to and learn from their human partners to accelerate operator learning.<\/p>\n<h3>Our Solution<\/h3>\n<p>We\u00a0sought to elucidate the feedback and feedforward control strategies used by\u00a0human operators to\u00a0supervise\u00a0these machines. We investigated this line of inquiry\u00a0by simulating\u00a0robotic teleoperation via\u00a0a path\u00a0following video game.<\/p>\n<p>Our preliminary results show that human operators learn and invert system dynamics while executing these teleoperation simulations. These data suggest that operators engage in model inversion, a process of\u00a0<em>defining a desired\u00a0output<\/em>\u00a0and\u00a0<em>internally planning an input<\/em>\u00a0to arrive at the intended\u00a0target.<\/p>\n<p>These results may provide insights towards developing\u00a0control interfaces\u00a0that can\u00a0adapt to their\u00a0human operators with high fidelity and guarantee reliably safe teleoperation.<\/p>\n<h3>Impact<\/h3>\n<p>The results from this study will help predict how human operators interact with novel systems, and provide a starting point for ensuring safe operation of these systems. In addition, this method can be extended to be used in the clinic as a method to measure motor learning for individuals with motor impairment.<\/p>\n<h3>Publications<\/h3>\n<p>M Yamagami, D Howell, E Roth, SA Burden. Contributions of feedforward and feedback control in a manual trajectory-tracking task. <em>2<sup>nd<\/sup> IFAC Conference on Cyber-Physical &amp; Human Systems<\/em>, Miami, USA, Dec 14-15, 2018.<\/p>\n<p><em>Affiliated Students and Faculty<\/em>: <a href=\"http:\/\/brl.ee.washington.edu\/about\/graduate-students\/\">Momona Yamagami<\/a>, <a href=\"http:\/\/brl.ee.washington.edu\/about\/graduate-students\/\">Ben Chasnov<\/a>,\u00a0<a href=\"http:\/\/faculty.washington.edu\/sburden\/bio\/\">Sam Burden\u00a0<\/a><\/p>\n<h3><em>Related Media:<\/em><\/h3>\n<p><iframe loading=\"lazy\" width=\"1200\" height=\"675\" src=\"https:\/\/www.youtube.com\/embed\/vSE6pNQD1Jk?feature=oembed\" frameborder=\"0\" allow=\"autoplay; encrypted-media\" allowfullscreen><\/iframe><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;\t\t\t\t<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Problem Human interaction with the physical world is increasingly mediated by intelligent machines, such as surgical robots and active prostheses \/ orthoses. While machines can be engineered to produce a high degree of accuracy for a given input, current models of human-computer interaction, specifically how humans learn to operate these machines are still under &#8230; <a title=\"Quantifying HCPS interactions\" class=\"read-more\" href=\"https:\/\/wp.ece.uw.edu\/brl\/neural-engineering\/quantifying-hcps-interactions\/\" aria-label=\"Read more about Quantifying HCPS interactions\">Read more<\/a><\/p>\n","protected":false},"author":40,"featured_media":0,"parent":24,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"inline_featured_image":false,"footnotes":""},"tags":[],"class_list":["post-2847","page","type-page","status-publish"],"_links":{"self":[{"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/pages\/2847","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/users\/40"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/comments?post=2847"}],"version-history":[{"count":0,"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/pages\/2847\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/pages\/24"}],"wp:attachment":[{"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/media?parent=2847"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wp.ece.uw.edu\/brl\/wp-json\/wp\/v2\/tags?post=2847"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}