{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T17:31:05Z","timestamp":1772040665130,"version":"3.50.1"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"International Max Planck Research School for Intelligent Systems"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1109\/lra.2021.3057055","type":"journal-article","created":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T21:29:10Z","timestamp":1612387750000},"page":"1439-1446","source":"Crossref","is-referenced-by-count":24,"title":["Robot Learning With Crash Constraints"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5764-6713","authenticated-orcid":false,"given":"Alonso","family":"Marco","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7340-2180","authenticated-orcid":false,"given":"Dominik","family":"Baumann","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9889-6543","authenticated-orcid":false,"given":"Majid","family":"Khadiv","sequence":"additional","affiliation":[]},{"given":"Philipp","family":"Hennig","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6458-9112","authenticated-orcid":false,"given":"Ludovic","family":"Righetti","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2785-2487","authenticated-orcid":false,"given":"Sebastian","family":"Trimpe","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref32","article-title":"Efficient multi-contact pattern generation with sequential convex approximations of the centroidal dynamics","author":"ponton","year":"2020"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2976639"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1504\/IJMMNO.2013.055204"},{"key":"ref10","first-page":"902","article-title":"Constrained bayesian optimization of combined interaction force\/task space controllers for manipulations","author":"drie\u00df","year":"0","journal-title":"Proc Int Conf Robot Automat"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/HUMANOIDS.2016.7803249"},{"key":"ref12","article-title":"Constrained bayesian optimization for automatic chemical design","author":"griffiths","year":"2017"},{"key":"ref13","article-title":"Bayesian optimization and semiparametric models with applications to assistive technology","author":"snoek","year":"2013"},{"key":"ref14","first-page":"250","article-title":"Bayesian optimization with unknown constraints","author":"gelbart","year":"0","journal-title":"Proc Conf Uncertainty Artif Intell"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1214\/lnms\/1215456182"},{"key":"ref16","first-page":"5549","article-title":"A general framework for constrained bayesian optimization using information-based search","volume":"17","author":"hern\u00e1ndez-lobato","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2014.901225"},{"key":"ref18","article-title":"Gaussian process optimization with failures: Classification and convergence proof","volume":"1","author":"bachoc","year":"2019","journal-title":"Version"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/BF01097516"},{"key":"ref28","article-title":"Gaussian probabilities and expectation propagation","author":"cunningham","year":"2011"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8461237"},{"key":"ref27","first-page":"2035","article-title":"Approximations for binary gaussian process classification","volume":"9","author":"nickisch","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s10472-015-9463-9"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2901308"},{"key":"ref29","first-page":"3627","article-title":"Max-value entropy search for efficient bayesian optimization","author":"wang","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/Humanoids43949.2019.9035003"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487144"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487170"},{"key":"ref2","author":"rasmussen","year":"2006","journal-title":"Gaussian Processes for Machine Learning"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917743795"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2494218"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10898-019-00860-4"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1214\/15-BA976"},{"key":"ref21","first-page":"467","article-title":"Optimization subject to hidden constraints via statistical emulation","volume":"7","author":"lee","year":"2011","journal-title":"Pacific J Optim"},{"key":"ref24","first-page":"8276","article-title":"Bayesian optimisation over multiple continuous and categorical inputs","author":"ru","year":"2020","journal-title":"Int Conf Mach Learn"},{"key":"ref23","first-page":"1222","article-title":"Bayesian optimization with binary auxiliary information","author":"zhang","year":"0","journal-title":"Proc Conf Uncertainty of Artificial Intelligence"},{"key":"ref26","first-page":"837","article-title":"Mind the nuisance: Gaussian process classification using privileged noise","author":"hern\u00e1ndez-lobato","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref25","first-page":"117","article-title":"The application of Bayesian methods for seeking the extremum","volume":"2","author":"mockus","year":"1978"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7083369\/9285111\/09345965.pdf?arnumber=9345965","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:54:17Z","timestamp":1652194457000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9345965\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4]]},"references-count":32,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/lra.2021.3057055","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4]]}}}