{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T19:07:42Z","timestamp":1780081662081,"version":"3.54.0"},"reference-count":56,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T00:00:00Z","timestamp":1707696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006751","name":"U.S. Army","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006751","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurorobot."],"abstract":"<jats:p>Human teams are able to easily perform collaborative manipulation tasks. However, simultaneously manipulating a large extended object for a robot and human is a difficult task due to the inherent ambiguity in the desired motion. Our approach in this paper is to leverage data from human-human dyad experiments to determine motion intent for a physical human-robot co-manipulation task. We do this by showing that the human-human dyad data exhibits distinct torque triggers for a lateral movement. As an alternative intent estimation method, we also develop a deep neural network based on motion data from human-human trials to predict future trajectories based on past object motion. We then show how force and motion data can be used to determine robot control in a human-robot dyad. Finally, we compare human-human dyad performance to the performance of two controllers that we developed for human-robot co-manipulation. We evaluate these controllers in three-degree-of-freedom planar motion where determining if the task involves rotation or translation is ambiguous.<\/jats:p>","DOI":"10.3389\/fnbot.2024.1291694","type":"journal-article","created":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T04:19:50Z","timestamp":1707711590000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads"],"prefix":"10.3389","volume":"18","author":[{"given":"Erich","family":"Mielke","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric","family":"Townsend","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Wingate","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John L.","family":"Salmon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc D.","family":"Killpack","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,2,12]]},"reference":[{"key":"B1","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1145\/3568162.3576969","article-title":"\u201cResolving conflicts during human-robot co-manipulation,\u201d","volume-title":"Proceedings of the 2023 ACM\/IEEE International Conference on Human-Robot Interaction","author":"Al-Saadi","year":"2023"},{"key":"B2","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1109\/TOH.2020.3034244","article-title":"A novel haptic feature set for the classification of interactive motor behaviors in collaborative object transfer","volume":"14","author":"Al-Saadi","year":"2020","journal-title":"IEEE Trans. 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