{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T19:04:19Z","timestamp":1777921459032,"version":"3.51.4"},"reference-count":29,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&D Program of China","award":["2024YFB4708900"],"award-info":[{"award-number":["2024YFB4708900"]}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62225309"],"award-info":[{"award-number":["62225309"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U24A20278"],"award-info":[{"award-number":["U24A20278"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62361166632"],"award-info":[{"award-number":["62361166632"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62503316"],"award-info":[{"award-number":["62503316"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"crossref","award":["2025M771686"],"award-info":[{"award-number":["2025M771686"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Ind. Electron."],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1109\/tie.2026.3654778","type":"journal-article","created":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T21:23:58Z","timestamp":1769721838000},"page":"8970-8982","source":"Crossref","is-referenced-by-count":0,"title":["Pretraining-Finetuning Framework for Efficient Codesign of Legged Robots"],"prefix":"10.1109","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4632-7001","authenticated-orcid":false,"given":"Ci","family":"Chen","sequence":"first","affiliation":[{"name":"School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, the State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, and Shanghai Key Laboratory of Navigation and Location Based Services, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6732-0734","authenticated-orcid":false,"given":"Yifei","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Automation Engineering, Shanghai University of Electric Power, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0895-1779","authenticated-orcid":false,"given":"Haoqi","family":"Han","sequence":"additional","affiliation":[{"name":"School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, the State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, and Shanghai Key Laboratory of Navigation and Location Based Services, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0981-935X","authenticated-orcid":false,"given":"Yue","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9318-9014","authenticated-orcid":false,"given":"Rong","family":"Xiong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9959-1634","authenticated-orcid":false,"given":"Hesheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, the State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, and Shanghai Key Laboratory of Navigation and Location Based Services, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.adh5401"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.adi7566"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2024.3360604"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2024.3429576"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3211785"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IROS55552.2023.10341983"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMECH.2023.3330427"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10161034"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3234809"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2017.XIII.003"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9560988"},{"key":"ref12","article-title":"Neural graph evolution: Towards efficient automatic robot design","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Wang","year":"2019"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-25874-z"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793537"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636415"},{"key":"ref16","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610200"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.010"},{"key":"ref19","article-title":"Isaac gym: High performance GPU based physics simulation for robot learning","volume-title":"Proc. 35th Conf. Neural Inf. Process. Syst. Datasets Benchmarks Track (Round 2)","author":"Makoviychuk","year":"2021"},{"key":"ref20","first-page":"34846","article-title":"Rethinking value function learning for generalization in reinforcement learning","volume":"35","author":"Moon","year":"2022","journal-title":"Proc. Adv. Neural Inf. Process. Syst."},{"key":"ref21","first-page":"2020","article-title":"Phasic policy gradient","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Cobbe","year":"2021"},{"key":"ref22","article-title":"High-dimensional continuous control using generalized advantage estimation","author":"Schulman","year":"2015"},{"key":"ref23","first-page":"138","article-title":"Deep whole-body control: Learning a unified policy for manipulation and locomotion","volume-title":"Proc. Conf. Robot Learn. (CoRL)","author":"Fu","year":"2022"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/iros60139.2025.11246368"},{"key":"ref25","first-page":"91","article-title":"Learning to walk in minutes using massively parallel deep reinforcement learning","volume-title":"Proc. Conf. Robot Learn.","author":"Rudin","year":"2022"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2024.3375086"},{"key":"ref27","first-page":"1893","article-title":"GenLoco: Generalized locomotion controllers for quadrupedal robots","volume-title":"Proc. Conf. Robot Learn.","author":"Feng","year":"2023"},{"key":"ref28","first-page":"20132","article-title":"A minimalist approach to offline reinforcement learning","volume":"34","author":"Fujimoto","year":"2021","journal-title":"Proc. Adv. Neural Inf. Process. Syst."},{"key":"ref29","first-page":"15084","article-title":"Decision transformer: Reinforcement learning via sequence modeling","volume":"34","author":"Chen","year":"2021","journal-title":"Proc. Adv. Neural Inf. Process. Syst."}],"container-title":["IEEE Transactions on Industrial Electronics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/41\/11503074\/11367814.pdf?arnumber=11367814","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T19:54:24Z","timestamp":1777665264000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11367814\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":29,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tie.2026.3654778","relation":{},"ISSN":["0278-0046","1557-9948"],"issn-type":[{"value":"0278-0046","type":"print"},{"value":"1557-9948","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6]]}}}