{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T03:50:40Z","timestamp":1791345040334,"version":"4.3.1"},"reference-count":38,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100018693","name":"Horizon Europe","doi-asserted-by":"publisher","award":["101070600"],"award-info":[{"award-number":["101070600"]}],"id":[{"id":"10.13039\/100018693","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Robotics and Autonomous Systems"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.robot.2026.105649","type":"journal-article","created":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T23:05:23Z","timestamp":1784934323000},"page":"105649","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A context-adaptive policy framework for robust and reactive robotic manipulation via uncertainty-aware imitation learning"],"prefix":"10.1016","volume":"205","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1062-6722","authenticated-orcid":false,"given":"Tim R.","family":"Winter","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9056-5912","authenticated-orcid":false,"given":"Leonard","family":"Kl\u00fcpfel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9201-6947","authenticated-orcid":false,"given":"Ashok M.","family":"Sundaram","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3002-7274","authenticated-orcid":false,"given":"Werner","family":"Friedl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1708-4223","authenticated-orcid":false,"given":"Maximo A.","family":"Roa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9555-9517","authenticated-orcid":false,"given":"Freek","family":"Stulp","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1428-8933","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Silv\u00e9rio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.robot.2026.105649_b1","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1146\/annurev-control-100819-063206","article-title":"Recent advances in robot learning from demonstration","volume":"3","author":"Ravichandar","year":"2020","journal-title":"Annu. Rev. Control. Robot. Auton. Syst."},{"key":"10.1016\/j.robot.2026.105649_b2","series-title":"Gaussian Processes for Machine Learning","first-page":"272","author":"Rasmussen","year":"2006"},{"issue":"5","key":"10.1016\/j.robot.2026.105649_b3","first-page":"943","article-title":"Learning stable nonlinear dynamical systems with Gaussian mixture models","volume":"27","author":"Khansari-Zadeh","year":"2011","journal-title":"TRO"},{"issue":"4","key":"10.1016\/j.robot.2026.105649_b4","first-page":"4452","article-title":"Bayesian Gaussian mixture model for robotic policy imitation","volume":"4","author":"Pignat","year":"2019","journal-title":"RA-L"},{"key":"10.1016\/j.robot.2026.105649_b5","series-title":"Proc. IEEE\/RSJ Intl Conf. on Intelligent Robots and Systems","first-page":"7778","article-title":"ILoSA: Interactive learning of stiffness and attractors","author":"Franzese","year":"2021"},{"issue":"3","key":"10.1016\/j.robot.2026.105649_b6","first-page":"6052","article-title":"Learning to pick at non-zero-velocity from interactive demonstrations","volume":"7","author":"Meszaros","year":"2022","journal-title":"RA-L"},{"key":"10.1016\/j.robot.2026.105649_b7","unstructured":"S.M. Khansari-Zadeh, SEDS & LASA Handwriting Dataset. URL https:\/\/cs.stanford.edu\/people\/khansari\/download.html."},{"issue":"2","key":"10.1016\/j.robot.2026.105649_b8","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1109\/TSMCB.2006.886952","article-title":"On learning, representing, and generalizing a task in a humanoid robot","volume":"37","author":"Calinon","year":"2007","journal-title":"IEEE Trans. Syst. Man Cybern. Part B (Cybernetics)"},{"issue":"1","key":"10.1016\/j.robot.2026.105649_b9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11370-015-0187-9","article-title":"A tutorial on task-parameterized movement learning and retrieval","volume":"9","author":"Calinon","year":"2015","journal-title":"Intell. Serv. Robot."},{"key":"10.1016\/j.robot.2026.105649_b10","series-title":"Proc. IEEE\/RSJ Intl Conf. on Intelligent Robots and Systems","first-page":"380","article-title":"Local Gaussian process regression for real-time model-based robot control","author":"Nguyen-Tuong","year":"2008"},{"key":"10.1016\/j.robot.2026.105649_b11","first-page":"958","article-title":"Using locally weighted regression for robot learning","volume":"vol. 2","author":"Atkeson","year":"1991"},{"issue":"2","key":"10.1016\/j.robot.2026.105649_b12","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1162\/NECO_a_00393","article-title":"Dynamical movement primitives: Learning attractor models for motor behaviors","volume":"25","author":"Ijspeert","year":"2013","journal-title":"Neural Comput."},{"key":"10.1016\/j.robot.2026.105649_b13","article-title":"Probabilistic movement primitives","volume":"vol. 26","author":"Paraschos","year":"2013"},{"issue":"7","key":"10.1016\/j.robot.2026.105649_b14","first-page":"833","article-title":"Kernelized movement primitives","volume":"38","author":"Huang","year":"2019","journal-title":"IJRR"},{"key":"10.1016\/j.robot.2026.105649_b15","series-title":"Proc. IEEE\/RSJ Intl Conf. on Intelligent Robots and Systems","article-title":"Learning bimanual end-effector poses from demonstrations using task-parameterized dynamical systems","author":"Silverio","year":"2015"},{"key":"10.1016\/j.robot.2026.105649_b16","series-title":"Proc. IEEE Intl Conf. on Humanoid Robots","article-title":"Learning compact parameterized skills with a single regression","author":"Stulp","year":"2013"},{"issue":"1","key":"10.1016\/j.robot.2026.105649_b17","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/s11370-017-0235-8","article-title":"Learning task-parameterized dynamic movement primitives using mixture of GMMs","volume":"11","author":"Pervez","year":"2017","journal-title":"Intell. Serv. Robot."},{"issue":"2","key":"10.1016\/j.robot.2026.105649_b18","first-page":"2163","article-title":"Active learning of Bayesian probabilistic movement primitives","volume":"6","author":"Kulak","year":"2021","journal-title":"RA-L"},{"key":"10.1016\/j.robot.2026.105649_b19","series-title":"Proc. IEEE Intl Conf. on Humanoid Robots","first-page":"351","article-title":"Incremental imitation learning of context-dependent motor skills","author":"Ewerton","year":"2016"},{"issue":"10\u201311","key":"10.1016\/j.robot.2026.105649_b20","first-page":"1684","article-title":"Diffusion policy: Visuomotor policy learning via action diffusion","volume":"44","author":"Chi","year":"2024","journal-title":"IJRR"},{"issue":"14","key":"10.1016\/j.robot.2026.105649_b21","doi-asserted-by":"crossref","first-page":"14754","DOI":"10.1609\/aaai.v39i14.33617","article-title":"FlowPolicy: Enabling fast and robust 3D flow-based policy via consistency flow matching for robot manipulation","volume":"39","author":"Zhang","year":"2025","journal-title":"AAAI"},{"key":"10.1016\/j.robot.2026.105649_b22","article-title":"Learning stochastically stable Gaussian process state-space models","volume":"12","author":"Umlauft","year":"2020","journal-title":"IFAC J. Syst. Control."},{"issue":"6","key":"10.1016\/j.robot.2026.105649_b23","first-page":"4520","article-title":"Learning a flexible neural energy function with a unique minimum for globally stable and accurate demonstration learning","volume":"39","author":"Jin","year":"2023","journal-title":"TRO"},{"issue":"5","key":"10.1016\/j.robot.2026.105649_b24","doi-asserted-by":"crossref","first-page":"3909","DOI":"10.1109\/TRO.2023.3289597","article-title":"Stable motion primitives via imitation and contrastive learning","volume":"39","author":"P\u00e9rez-Dattari","year":"2023","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.robot.2026.105649_b25","series-title":"Proceedings of the 33rd International Conference on Neural Information Processing Systems","article-title":"Learning stable deep dynamics models","author":"Manek","year":"2019"},{"key":"10.1016\/j.robot.2026.105649_b26","series-title":"2024 IEEE International Conference on Robotics and Automation","first-page":"17216","article-title":"Learning complex motion plans using neural ODEs with safety and stability guarantees","author":"Nawaz","year":"2024"},{"key":"10.1016\/j.robot.2026.105649_b27","series-title":"Proceedings of the 7th Conference on Robot Learning","first-page":"3485","article-title":"Task generalization with stability guarantees via elastic dynamical system motion policies","volume":"vol. 229","author":"Li","year":"2023"},{"key":"10.1016\/j.robot.2026.105649_b28","series-title":"2024 IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"5152","article-title":"Se(3) linear parameter varying dynamical systems for globally asymptotically stable end-effector control","author":"Sun","year":"2024"},{"key":"10.1016\/j.robot.2026.105649_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102379","article-title":"Fusion dynamical systems with machine learning in imitation learning: A comprehensive overview","volume":"108","author":"Hu","year":"2024","journal-title":"Inf. Fusion"},{"issue":"1","key":"10.1016\/j.robot.2026.105649_b30","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1162\/neco.1991.3.1.79","article-title":"Adaptive mixtures of local experts","volume":"3","author":"Jacobs","year":"1991","journal-title":"Neural Comput."},{"issue":"3","key":"10.1016\/j.robot.2026.105649_b31","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10994-021-05946-3","article-title":"Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods","volume":"110","author":"H\u00fcllermeier","year":"2021","journal-title":"Mach. Learn."},{"key":"10.1016\/j.robot.2026.105649_b32","first-page":"1","article-title":"Products of experts","volume":"vol. 1999","author":"Hinton","year":"1999"},{"issue":"2","key":"10.1016\/j.robot.2026.105649_b33","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1177\/02783649211040561","article-title":"Learning from demonstration using products of experts: Applications to manipulation and task prioritization","volume":"41","author":"Pignat","year":"2021","journal-title":"Int. J. Robot. Res."},{"issue":"12","key":"10.1016\/j.robot.2026.105649_b34","doi-asserted-by":"crossref","first-page":"10732","DOI":"10.1109\/LRA.2024.3477169","article-title":"Conditional neural expert processes for learning movement primitives from demonstration","volume":"9","author":"Yildirim","year":"2024","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.robot.2026.105649_b35","series-title":"The CMA evolution strategy: A tutorial","author":"Hansen","year":"2016"},{"key":"10.1016\/j.robot.2026.105649_b36","series-title":"IEEE\/CVF Conf. on Computer Vision and Pattern Recognition","first-page":"7464","article-title":"YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","author":"Wang","year":"2023"},{"key":"10.1016\/j.robot.2026.105649_b37","series-title":"Proc. IEEE\/RSJ Intl Conf. on Intelligent Robots and Systems","first-page":"10749","article-title":"6D object pose estimation from approximate 3D models for orbital robotics","author":"Ulmer","year":"2023"},{"key":"10.1016\/j.robot.2026.105649_b38","series-title":"Closing the Loop: 3D Object Tracking for Advanced Robotic Manipulation","first-page":"172","author":"Stoiber","year":"2023"}],"container-title":["Robotics and Autonomous Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0921889026003210?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0921889026003210?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T03:09:43Z","timestamp":1791342583000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0921889026003210"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":38,"alternative-id":["S0921889026003210"],"URL":"https:\/\/doi.org\/10.1016\/j.robot.2026.105649","relation":{},"ISSN":["0921-8890"],"issn-type":[{"value":"0921-8890","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A context-adaptive policy framework for robust and reactive robotic manipulation via uncertainty-aware imitation learning","name":"articletitle","label":"Article Title"},{"value":"Robotics and Autonomous Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.robot.2026.105649","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"105649"}}