{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T08:48:01Z","timestamp":1782809281482,"version":"3.54.5"},"reference-count":0,"publisher":"ECMS","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,23]]},"abstract":"<jats:p>Robotics has progressed from isolated industrial manipulators to systems capable of fluid interaction, collaboration, and ultimately teaming with humans. This trajectory\u2014from Human\u2011Robot Interaction (HRI) to Human\u2011Robot Collaboration (HRC) and Human\u2011Robot Teaming (HRT) reflects increasing autonomy, shared decision\u2011making and mutual adaptation. Within this evolution, imitation learning (IL) has become a key enabler for intuitive and efficient cooperation, allowing robots to acquire human strategies directly from demonstrations and operate effectively in dynamic, unstructured environments. This review outlines the technological foundations supporting this shift, including advances in sensing, actuation, and both classical and AI\u2011driven control. By synthesizing current methods and emerging trends, the paper provides an overview of the state-of-the-art and highlights IL as a promising pathway toward seamless HRT.<\/jats:p>","DOI":"10.7148\/2026-0161","type":"proceedings-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T08:36:46Z","timestamp":1782808606000},"page":"161-168","source":"Crossref","is-referenced-by-count":0,"title":["Imitation learning for human\u2013robot teaming in battery disassembly: enabling technologies and a collaborative manipulation pipeline"],"prefix":"10.7148","author":[{"given":"Filippo","family":"Sanfilippo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cecilia","family":"Scoccia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4144","published-online":{"date-parts":[[2026,6,23]]},"event":{"name":"40th ECMS International Conference on Modelling and Simulation"},"container-title":["ECMS 2026 Proceedings edited by Filippo Sanfilippo, Florenc Demrozi, Fabio Sgarbossa, Mohammad Poursina"],"original-title":[],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T08:36:53Z","timestamp":1782808613000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.scs-europe.net\/dlib\/2026\/ecms2026acceptedpapers\/0161_hric_ecms2026_0118.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,23]]},"references-count":0,"URL":"https:\/\/doi.org\/10.7148\/2026-0161","relation":{},"subject":[],"published":{"date-parts":[[2026,6,23]]}}}