{"id":1074,"date":"2026-07-03T11:48:57","date_gmt":"2026-07-03T15:48:57","guid":{"rendered":"https:\/\/web.uri.edu\/icrl\/?p=1074"},"modified":"2026-07-09T14:36:51","modified_gmt":"2026-07-09T18:36:51","slug":"1074-2","status":"publish","type":"post","link":"https:\/\/web.uri.edu\/icrl\/1074-2\/","title":{"rendered":"Automated Nut Threading"},"content":{"rendered":"\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"975\" height=\"627\" src=\"https:\/\/web.uri.edu\/icrl\/wp-content\/uploads\/sites\/2260\/Camera-2.jpg\" alt=\"\" class=\"wp-image-1083\" style=\"aspect-ratio:1.5550615273820334;width:655px;height:auto\" srcset=\"https:\/\/web.uri.edu\/icrl\/wp-content\/uploads\/sites\/2260\/Camera-2.jpg 975w, https:\/\/web.uri.edu\/icrl\/wp-content\/uploads\/sites\/2260\/Camera-2-300x193.jpg 300w, https:\/\/web.uri.edu\/icrl\/wp-content\/uploads\/sites\/2260\/Camera-2-768x494.jpg 768w, https:\/\/web.uri.edu\/icrl\/wp-content\/uploads\/sites\/2260\/Camera-2-364x234.jpg 364w, https:\/\/web.uri.edu\/icrl\/wp-content\/uploads\/sites\/2260\/Camera-2-500x322.jpg 500w\" sizes=\"auto, (max-width: 975px) 100vw, 975px\" \/><\/figure>\n\n\n\n<div style=\"height:67px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p>This project developed a novel robotic system designed to automate the initial mating of nuts on threaded studs by integrating convolutional neural networks, image processing, and force sensing. The YOLO architecture was employed to develop a convolutional neural network (CNN) to identify studs and studs with threaded nuts. Visual servoing that combines CNN with traditional image processing techniques aligned the nut and stud before threading. A novel force servoing technique, utilizing a 6-axis force sensor, was implemented to maintain concentric alignment throughout the threading process. This approach allows the robot to detect cross-threading and adjust for it without stopping the process, unlike previous works on this problem. The system was tested in 100 threading cases, achieving a 97% success rate for threading a nut on the stud, with 95% of the cases performed autonomously.<\/p>\n\n\n\n<p>Reference:<\/p>\n\n\n\n<p>Wellington, K., Jouaneh,&nbsp; M., Tingley,&nbsp; J., Stegagno, P., and Lanzi, S.&nbsp;Vision and force-guided robotic system for autonomous nut threading with cross-threading detection, <em>Robotics and Autonomous Systems<\/em>, Volume 203, 2026, 105459,&nbsp;<a href=\"https:\/\/doi.org\/10.1016\/j.robot.2026.105459\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/doi.org\/10.1016\/j.robot.2026.105459<\/a>.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This project developed a novel robotic system designed to automate the initial mating of nuts on threaded studs by integrating convolutional neural networks, image processing, and force sensing. The YOLO architecture was employed to develop a convolutional neural network (CNN) to identify studs and studs with threaded nuts. Visual servoing that combines CNN with traditional [&hellip;]<\/p>\n","protected":false},"author":4282,"featured_media":1079,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[3,29,8,9],"tags":[17,19,16],"class_list":["post-1074","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industrial-automation","category-jouaneh","category-research","category-stegagno","tag-jouaneh","tag-stegagno","tag-automation"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/posts\/1074","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/users\/4282"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/comments?post=1074"}],"version-history":[{"count":5,"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/posts\/1074\/revisions"}],"predecessor-version":[{"id":1160,"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/posts\/1074\/revisions\/1160"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/media\/1079"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/media?parent=1074"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/categories?post=1074"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/icrl\/wp-json\/wp\/v2\/tags?post=1074"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}