{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T11:24:13Z","timestamp":1780053853488,"version":"3.54.0"},"reference-count":46,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["IIS 1956027,IIS-2132972,CCF-2110861"],"award-info":[{"award-number":["IIS 1956027,IIS-2132972,CCF-2110861"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,23]]},"DOI":"10.1109\/icra46639.2022.9812135","type":"proceedings-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T19:36:40Z","timestamp":1657654600000},"page":"3230-3237","source":"Crossref","is-referenced-by-count":7,"title":["A Recurrent Differentiable Engine for Modeling Tensegrity Robots Trainable with Low-Frequency Data"],"prefix":"10.1109","author":[{"given":"Kun","family":"Wang","sequence":"first","affiliation":[{"name":"Rutgers University,Department of Computer Science,NJ,USA,08901"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mridul","family":"Aanjaneya","sequence":"additional","affiliation":[{"name":"Rutgers University,Department of Computer Science,NJ,USA,08901"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kostas","family":"Bekris","sequence":"additional","affiliation":[{"name":"Rutgers University,Department of Computer Science,NJ,USA,08901"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"1162","article-title":"Active domain randomization","author":"mehta","year":"2020","journal-title":"Conference on Robot Learning"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3062303"},{"key":"ref33","article-title":"Adaptive Tensegrity Locomotion: Controlling a Compliant Icosahe-dron with Symmetry-Reduced Reinforcement Learning","author":"surovik","year":"2019","journal-title":"International Journal of Robotics Research (IJRR)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8463144"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989079"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12235"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793789"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1098\/rsif.2014.0520"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7354134"},{"key":"ref34","year":"0","journal-title":"NASA tensegrity robotics toolkit"},{"key":"ref10","author":"lutter","year":"2020","journal-title":"A differentiable newton euler algorithm for multi-body model learning"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6386109"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561805"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636783"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3414685.3417766","article-title":"Add: analytically differentiable dynamics for multi-body systems with frictional contact","volume":"39","author":"geilinger","year":"2020","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2019.00006"},{"key":"ref15","article-title":"Difftaichi: Differentiable programming for physical simulation","author":"hu","year":"0","journal-title":"ICLRE"},{"key":"ref16","article-title":"Scalable differentiable physics for learning and control","author":"qiao","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aau5872"},{"key":"ref18","first-page":"651","article-title":"A first principles approach for data-efficient system identification of spring-rod systems via differentiable physics engines","volume":"120","author":"wang","year":"2020","journal-title":"Proceedings of the 2nd Conference on Learning for Dynamics and Control"},{"key":"ref19","first-page":"804","article-title":"Encoding physical constraints in differentiable newton-euler algorithm","author":"sutanto","year":"2020","journal-title":"Learning for Dynamics and Control"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3063702"},{"key":"ref4","article-title":"Superball: Exploring tensegrities for planetary probes","author":"bruce","year":"0","journal-title":"12th International Symposium on Artificial Intelligence Robotics and Automation in Space (i-SAIRAS)"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01518"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechrescom.2020.103480"},{"key":"ref6","first-page":"4470","article-title":"Graph networks as learnable physics engines for inference and control","author":"sanchez-gonzalez","year":"2018","journal-title":"International Conference on Machine Learning"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01530"},{"key":"ref5","article-title":"Interaction networks for learning about objects, relations and physics","volume":"29","author":"battaglia","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref8","first-page":"7178","article-title":"End-to-end differentiable physics for learning and control","author":"de avila belbute-peres","year":"0","journal-title":"Advances in neural information processing systems"},{"key":"ref7","article-title":"Flexible neural representation for physics prediction","volume":"31","author":"mrowca","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref2","article-title":"Design, simulation, and testing of a flexible actuated spine for quadruped robots","author":"sabelhaus","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3062323"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2016.7759811"},{"key":"ref46","first-page":"1071","article-title":"Learning neural network policies with guided policy search under unknown dynamics","volume":"27","author":"levine","year":"2014","journal-title":"NIPS"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.044"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001921"},{"key":"ref22","article-title":"Interactive differentiable simulation","author":"heiden","year":"2019","journal-title":"ArXiv Preprint"},{"key":"ref21","article-title":"gradsim: Differentiable simulation for system identification and visuomotor control","author":"murthy","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8594374"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3070305"},{"key":"ref41","first-page":"95","article-title":"Two-way coupling of rigid and deformable bodies","author":"shinar","year":"2008","journal-title":"Proceedings of the 2008 ACM SIGGRAPH\/Eurographics Symposium on Computer Animation"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2021.XVII.067"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/B978-0-444-53859-8.00003-5","article-title":"The cross-entropy method for optimization","volume":"31","author":"botev","year":"2013","journal-title":"Handbook of Statistics"},{"key":"ref26","article-title":"Differentiable molecular simulations for control and learning","author":"wang","year":"0","journal-title":"ICLR 2020 Workshop on Integration of Deep Neural Models and Differential Equations"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1287\/opre.6.2.244"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s43154-021-00052-7"}],"event":{"name":"2022 IEEE International Conference on Robotics and Automation (ICRA)","location":"Philadelphia, PA, USA","start":{"date-parts":[[2022,5,23]]},"end":{"date-parts":[[2022,5,27]]}},"container-title":["2022 International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9811522\/9811357\/09812135.pdf?arnumber=9812135","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T23:04:11Z","timestamp":1667516651000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9812135\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/icra46639.2022.9812135","relation":{},"subject":[],"published":{"date-parts":[[2022,5,23]]}}}