{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:02:14Z","timestamp":1775325734248,"version":"3.50.1"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002855","name":"National Science and Technology Major Project of the Ministry of Science and Technology of China","doi-asserted-by":"publisher","award":["2018AAA0102900"],"award-info":[{"award-number":["2018AAA0102900"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"name":"\u201cNew Generation Artificial Intelligence\u201d Key Field Research and Development Plan of Guangdong Province","award":["2021B0101410002"],"award-info":[{"award-number":["2021B0101410002"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62133013"],"award-info":[{"award-number":["62133013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1109\/tcyb.2024.3368148","type":"journal-article","created":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T18:45:56Z","timestamp":1712342756000},"page":"3852-3863","source":"Crossref","is-referenced-by-count":14,"title":["Digital-Twin-Assisted Skill Learning for 3C Assembly Tasks"],"prefix":"10.1109","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3546-6305","authenticated-orcid":false,"given":"Fuchun","family":"Sun","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6623-0799","authenticated-orcid":false,"given":"Naijun","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1845-4217","authenticated-orcid":false,"given":"Xinzhou","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Tongji University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1884-7114","authenticated-orcid":false,"given":"Ruize","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Virtual Reality Technology and Systems and the Jiangxi Research Institute, Beihang University, Beijing, China"}]},{"given":"Shengyi","family":"Miao","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8245-0184","authenticated-orcid":false,"given":"Zengxin","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9149-7336","authenticated-orcid":false,"given":"Bin","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4042-6044","authenticated-orcid":false,"given":"Huaping","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4557-9066","authenticated-orcid":false,"given":"Yongjia","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Virtual Reality Technology and Systems and the Jiangxi Research Institute, Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1104-2444","authenticated-orcid":false,"given":"Haiming","family":"Huang","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-89092-6_27"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1142\/S021962202350013X"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-019-2648-7"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/app10051555"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WRC-SARA.2019.8931930"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/AIM.2019.8868827"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/WRC-SARA.2019.8931947"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/RCAR52367.2021.9517545"},{"key":"ref9","first-page":"12","article-title":"Robot learning from demonstration","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"97","author":"Atkeson"},{"key":"ref10","first-page":"1","article-title":"Generative adversarial imitation learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ho"},{"key":"ref11","first-page":"883","article-title":"Provable hierarchical imitation learning via EM","volume-title":"Proc. Int. Conf. Artif. Intell. Stat.","author":"Zhang"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794127"},{"key":"ref13","first-page":"1","article-title":"Hindsight experience replay","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Andrychowicz"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2022.3211440"},{"key":"ref15","first-page":"5097","article-title":"Adversarial option-aware hierarchical imitation learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Jing"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.009"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3150802"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.15607\/rss.2023.xix.025"},{"key":"ref19","first-page":"1","article-title":"VIMA: General robot manipulation with multimodal prompts","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Jiang"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.jii.2021.100289"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2022.119986"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-022-09118-y"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2022.101676"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3390\/machines10050388"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.compind.2022.103667"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3237042"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2023.102601"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2023.3255991"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/HUMANOIDS.2015.7363441"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340781"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2022.3141105"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ITT56123.2022.9863938"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMECH.2018.2799963"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2017.2783342"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2017.10.002"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2018.10.005"},{"key":"ref37","article-title":"Relational inductive biases, deep learning, and graph networks","author":"Battaglia","year":"2018","journal-title":"arXiv:1806.01261"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2949221"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00369"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3021756"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107039"},{"issue":"1","key":"ref42","first-page":"1395","article-title":"A review of robot learning for manipulation: Challenges, representations, and algorithms","volume":"22","author":"Kroemer","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1080\/00222899809601335"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2016.7759434"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.26599\/TST.2018.9010096"},{"key":"ref46","first-page":"1025","article-title":"Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning","volume-title":"Proc. Conf. Robot Learn.","author":"Gupta"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2020.XVI.061"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2015.02.003"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/3272127.3275048"},{"key":"ref50","first-page":"2917","article-title":"Hierarchical imitation and reinforcement learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Le"},{"key":"ref51","first-page":"1","article-title":"Data-efficient hierarchical reinforcement learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Nachum"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aav3123"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917710318"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2023.3298195"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202133"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6386109"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1115\/1.4011045"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1086\/131801"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/2384716.2384777"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01646"},{"key":"ref61","first-page":"1861","article-title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Haarnoja"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11775"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/10595515\/10492985.pdf?arnumber=10492985","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T18:56:24Z","timestamp":1732906584000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10492985\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7]]},"references-count":62,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2024.3368148","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7]]}}}