{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T14:29:28Z","timestamp":1773844168979,"version":"3.50.1"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"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":[[2021,5,30]]},"DOI":"10.1109\/icra48506.2021.9561561","type":"proceedings-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:28:35Z","timestamp":1634689715000},"page":"5914-5920","source":"Crossref","is-referenced-by-count":28,"title":["Scalable Learning of Safety Guarantees for Autonomous Systems using Hamilton-Jacobi Reachability"],"prefix":"10.1109","author":[{"given":"Sylvia","family":"Herbert","sequence":"first","affiliation":[]},{"given":"Jason J.","family":"Choi","sequence":"additional","affiliation":[]},{"given":"Suvansh","family":"Sanjeev","sequence":"additional","affiliation":[]},{"given":"Marsalis","family":"Gibson","sequence":"additional","affiliation":[]},{"given":"Koushil","family":"Sreenath","sequence":"additional","affiliation":[]},{"given":"Claire J.","family":"Tomlin","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref38","article-title":"Berkeley Efficient API in C++ for Level Set methods","author":"tenabe","year":"0"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/MMAR.2017.8046794"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.21236\/ADA572108"},{"key":"ref31","article-title":"Multi-resolution A*","author":"du","year":"2020"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9991(89)90035-1"},{"key":"ref37","article-title":"Optimized Dynamic Programming Toolbox","author":"chen","year":"0"},{"key":"ref36","article-title":"Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor","volume":"80","author":"haarnoja","year":"2018","journal-title":"Machine Learning Research"},{"key":"ref35","author":"pong","year":"0","journal-title":"RLkit"},{"key":"ref34","article-title":"Crazyflie Packages","author":"fridovich-keil","year":"0"},{"key":"ref10","article-title":"Learning stable deep dynamics models","author":"kolter","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref11","article-title":"Safe learning-based trajectory tracking for underactuated vehicles with partially unknown dynamics","author":"beckers","year":"2020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2020.XVI.088"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CDC.2014.7039601"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2018.2876389"},{"key":"ref15","article-title":"Safe model-based reinforcement learning with stability guarantees","author":"berkenkamp","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013387"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2017.2753460"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.23919\/ACC.2019.8814865"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2013.02.003"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/BF00993591"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.23919\/ECC.2019.8796030"},{"key":"ref27","article-title":"A minimum discounted reward hamilton-jacobi formulation for computing reachable sets","author":"akametalu","year":"2018"},{"key":"ref3","article-title":"A lyapunov-based approach to safe reinforcement learning","author":"chow","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref6","article-title":"The lyapunov neural network: Adaptive stability certification for safe learning of dynamical systems","author":"richards","year":"2018"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/S0010-4655(99)00501-9"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CDC.2017.8263977"},{"key":"ref8","article-title":"Excursion search for constrained bayesian optimization under a limited budget of failures","author":"marco","year":"2020"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ECC.2015.7330915"},{"key":"ref2","article-title":"Uncertainty-aware reinforcement learning for collision avoidance","author":"kahn","year":"2017","journal-title":"arXiv preprint arXiv 1702 08608"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CDC40024.2019.9030133"},{"key":"ref1","article-title":"Constrained policy optimization","author":"achiam","year":"2017"},{"key":"ref20","article-title":"Safe reinforcement learning for probabilistic reachability and safety specifications: A Lyapunov-based approach","author":"huh","year":"2020"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CDC40024.2019.9029575"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2018.2797194"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/2728606.2728612"},{"key":"ref23","author":"quigley","year":"2009","journal-title":"ROS An Open-source Robot Operating System"},{"key":"ref26","article-title":"Exact and efficient Hamilton-Jacobi-based guaranteed safety analysis via system decomposition","author":"chen","year":"2016","journal-title":"IEEE Int Conf Robotics and Automation"},{"key":"ref25","article-title":"Gaussian processes in machine learning","author":"rasmussen","year":"2003","journal-title":"Machine Learning Summer School"}],"event":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","location":"Xi'an, China","start":{"date-parts":[[2021,5,30]]},"end":{"date-parts":[[2021,6,5]]}},"container-title":["2021 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9560720\/9560666\/09561561.pdf?arnumber=9561561","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:47:11Z","timestamp":1652197631000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9561561\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,30]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/icra48506.2021.9561561","relation":{},"subject":[],"published":{"date-parts":[[2021,5,30]]}}}