{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T21:28:55Z","timestamp":1775165335154,"version":"3.50.1"},"reference-count":39,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T00:00:00Z","timestamp":1685318400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T00:00:00Z","timestamp":1685318400000},"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":[[2023,5,29]]},"DOI":"10.1109\/icra48891.2023.10161144","type":"proceedings-article","created":{"date-parts":[[2023,7,4]],"date-time":"2023-07-04T17:20:56Z","timestamp":1688491256000},"page":"5078-5084","source":"Crossref","is-referenced-by-count":121,"title":["DreamWaQ: Learning Robust Quadrupedal Locomotion With Implicit Terrain Imagination via Deep Reinforcement Learning"],"prefix":"10.1109","author":[{"given":"I Made","family":"Aswin Nahrendra","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST),Daejeon,Republic of Korea,34141"}]},{"given":"Byeongho","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST),Daejeon,Republic of Korea,34141"}]},{"given":"Hyun","family":"Myung","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST),Daejeon,Republic of Korea,34141"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abk2822"},{"key":"ref35","article-title":"Fast and accurate deep network learning by exponential linear units (ELUs)","author":"clevert","year":"0","journal-title":"Proc International Conference on Learning Representations (ICLR)"},{"key":"ref12","first-page":"91","article-title":"Learning to walk in minutes using massively parallel deep reinforcement learning","author":"rudin","year":"0","journal-title":"Proc Conference on Robot Learning (CoRL)"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref15","first-page":"1291","article-title":"Visual-locomotion: Learning to walk on complex terrains with vision","author":"yu","year":"0","journal-title":"Proc Conference on Robot Learning (CoRL)"},{"key":"ref37","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"0","journal-title":"Proc International Conference on Learning Representations (ICLR)"},{"key":"ref14","first-page":"17273","article-title":"Coupling vision and proprioception for navigation of legged robots","author":"fu","year":"0","journal-title":"Proc IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref36","article-title":"Isaac Gym: High performance GPU-based physics simulation for robot learning","author":"makoviychuk","year":"2021","journal-title":"Advances in Neural Information Processing Systems Track on Datasets and Benchmarks"},{"key":"ref31","author":"kingma","year":"2013","journal-title":"Auto-encoding variational bayes"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aau5872"},{"key":"ref11"},{"key":"ref33","article-title":"Understanding disentangling in ? - VAE","author":"burgess","year":"0","journal-title":"Advances in Neural Information Processing (NeurIPS) Workshop on Learning Disentangled Representations"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206174"},{"key":"ref32","article-title":"? - VAE: Learning basic visual concepts with a constrained variational framework","author":"higgins","year":"0","journal-title":"Proc International Conference on Learning Representations (ICLR)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793865"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2016.7758092"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3182096"},{"key":"ref39","year":"0","journal-title":"H-RTK F9P Helical GPS"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3093009"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2020.XVI.064"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abc5986"},{"key":"ref18","author":"lee","year":"2022","journal-title":"Patchwork++ Fast and robust ground segmentation solving partial under-segmentation using 3D point cloud"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"4630","DOI":"10.1109\/LRA.2022.3151396","article-title":"Concurrent training of a control policy and a state estimator for dynamic and robust legged locomotion","volume":"7","author":"ji","year":"2022","journal-title":"IEEE l of Robotics and Automation"},{"key":"ref23","article-title":"Rapid locomotion via reinforcement learning","author":"margolis","year":"0","journal-title":"Proc Robotics Science and Systems"},{"key":"ref26","year":"0","journal-title":"Unitree AI"},{"key":"ref25","article-title":"Learning invariant representations for reinforcement learning without reconstruction","author":"zhang","year":"0","journal-title":"Proc International Conference on Learning Representations (ICLR)"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2021.XVII.011"},{"key":"ref22","author":"escontrela","year":"2022","journal-title":"Adversarial motion priors make good substitutes for complex reward functions"},{"key":"ref21","first-page":"928","article-title":"Minimizing energy consumption leads to the emergence of gaits in legged robots","author":"fu","year":"0","journal-title":"Proc Conference on Robot Learning (CoRL)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.008"},{"key":"ref27","first-page":"66","article-title":"Learning by cheating","author":"chen","year":"0","journal-title":"Proc Conference on Robot Learning (CoRL)"},{"key":"ref29","author":"schulman","year":"2017","journal-title":"Proximal policy optimization algorithms"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2013.6697236"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3150844"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989557"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-9460-1_18"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811755"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.23919\/ICCAS52745.2021.9650025"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abp9742"}],"event":{"name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","location":"London, United Kingdom","start":{"date-parts":[[2023,5,29]]},"end":{"date-parts":[[2023,6,2]]}},"container-title":["2023 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10160211\/10160212\/10161144.pdf?arnumber=10161144","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T17:33:15Z","timestamp":1690219995000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10161144\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,29]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/icra48891.2023.10161144","relation":{},"subject":[],"published":{"date-parts":[[2023,5,29]]}}}