{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T20:59:51Z","timestamp":1773521991494,"version":"3.50.1"},"reference-count":48,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,1]]},"DOI":"10.1109\/iros55552.2023.10342096","type":"proceedings-article","created":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T19:17:55Z","timestamp":1702495075000},"page":"8155-8162","source":"Crossref","is-referenced-by-count":6,"title":["Learning Compliant Stiffness by Impedance Control-Aware Task Segmentation and Multi-Objective Bayesian Optimization with Priors"],"prefix":"10.1109","author":[{"given":"Masashi","family":"Okada","sequence":"first","affiliation":[{"name":"Panasonic Holdings Corporation,Digital & AI Technology Center, Technology Division,Japan"}]},{"given":"Mayumi","family":"Komatsu","sequence":"additional","affiliation":[{"name":"Panasonic Holdings Corporation,Robotics Promotion Office, Manufacturing Innovation Division,Japan"}]},{"given":"Ryo","family":"Okumura","sequence":"additional","affiliation":[{"name":"Panasonic Holdings Corporation,Digital & AI Technology Center, Technology Division,Japan"}]},{"given":"Tadahiro","family":"Taniguchi","sequence":"additional","affiliation":[{"name":"Ritsumeikan University, College of Information Science and Engineering,Japan"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2015.2430053"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2016.2593492"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/tro.2022.3216078"},{"key":"ref4","article-title":"\u03c0-BO: Augmenting acquisition functions with user beliefs for bayesian optimization","volume-title":"ICLR","author":"Hvarfner","year":"2022"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793542"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2023.10.1748"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/machines11010035"},{"key":"ref8","article-title":"Reinforcement learning and the reward engineering prin-ciple","volume-title":"2014 AAAI Spring Symposium Series","author":"Dewey","year":"2014"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1177\/0278364911402527"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IROS47612.2022.9981728"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2020.12.2687"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636828"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86523-8_17"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2020.590681"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8968201"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.3011379"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3060389"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3191070"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2884240"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICINFA.2008.4608043"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1080\/00423114.2011.564289"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1115\/DSCC2015-9794"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1177\/0278364911428653"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s11370-015-0187-9"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917743319"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2011.6094676"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917713116"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487607"},{"key":"ref29","article-title":"Hierarchical decomposition of non-linear dynamics and control for system identification and policy distillation","author":"Abdulsamad","year":"2020","journal-title":"Learning for Dynamics and Control"},{"key":"ref30","article-title":"TACO: Learning task decomposition via temporal alignment for control","volume-title":"ICML","author":"Shiarlis","year":"2018"},{"key":"ref31","article-title":"Discovering motor programs by recomposing demonstrations","volume-title":"ICLR","author":"Shankar","year":"2019"},{"key":"ref32","article-title":"Compile: Compositional imitation learning and execution","author":"Kipf","year":"2019","journal-title":"I CML"},{"key":"ref33","article-title":"Learning robot skills with temporal variational inference","volume-title":"ICML","author":"Shankar","year":"2020"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3068891"},{"key":"ref35","article-title":"Bayesian nonparametrics for offline skill discovery","volume-title":"ICML","author":"Villecroze","year":"2022"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2013.6630691"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2022.06.052"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CDC.2016.7799085"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CASE49997.2022.9926713"},{"key":"ref40","article-title":"robosuite: A modular simulation framework and benchmark for robot learning","author":"Zhu","year":"2020","journal-title":"arXiv preprint"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2003.1242165"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3190806"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2021.3116855"},{"issue":"4","key":"ref44","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1023\/A:1008306431147","article-title":"Efficient global optimization of expensive black-box functions","volume":"13","author":"Jones","year":"1998","journal-title":"Journal of Global optimization"},{"key":"ref45","volume-title":"NeurIPS","author":"Bergstra","year":"2011"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3389817"},{"key":"ref47","article-title":"Switching kalman filter","volume-title":"tech. rep., The University of British Columbia","author":"Murphy","year":"1998"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2010.2102756"}],"event":{"name":"2023 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","location":"Detroit, MI, USA","start":{"date-parts":[[2023,10,1]]},"end":{"date-parts":[[2023,10,5]]}},"container-title":["2023 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10341341\/10341342\/10342096.pdf?arnumber=10342096","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T00:14:56Z","timestamp":1703031296000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10342096\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,1]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/iros55552.2023.10342096","relation":{},"subject":[],"published":{"date-parts":[[2023,10,1]]}}}