{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T21:52:23Z","timestamp":1767995543750,"version":"3.49.0"},"reference-count":37,"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"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,23]]},"DOI":"10.1109\/icra46639.2022.9812011","type":"proceedings-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T15:36:40Z","timestamp":1657640200000},"page":"4730-4736","source":"Crossref","is-referenced-by-count":14,"title":["Learning Crowd-Aware Robot Navigation from Challenging Environments via Distributed Deep Reinforcement Learning"],"prefix":"10.1109","author":[{"given":"Sango","family":"Matsuzaki","sequence":"first","affiliation":[{"name":"Honda R&D Co., LTD."}]},{"given":"Yuji","family":"Hasegawa","sequence":"additional","affiliation":[{"name":"Honda R&D Co., LTD."}]}],"member":"263","reference":[{"key":"ref33","article-title":"Graph attention networks","author":"veli?kovi?","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref32","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref31","first-page":"60","article-title":"Personal space modeling for human-computer interaction","author":"amaoka","year":"2009","journal-title":"International Conference on Entertainment Computing"},{"key":"ref30","volume":"609","author":"hall","year":"1966","journal-title":"The Hidden Dimension"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/100.580977"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"mnih","year":"2015","journal-title":"Nature"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10295"},{"key":"ref34","first-page":"1928","article-title":"Asynchronous methods for deep reinforcement learning","author":"mnih","year":"2016","journal-title":"International Conference on Machine Learning"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794134"},{"key":"ref11","article-title":"Fully distributed multi-robot collision avoidance via deep reinforcement learning for safe and efficient navigation in complex scenarios","author":"fan","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-642-19457-3_1","article-title":"Reciprocal n-body collision avoidance","author":"van den berg","year":"2011","journal-title":"Robotics Research"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32723-0_15"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2008.4543489"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1177\/027836499801700706"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.51.4282"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197148"},{"key":"ref18","article-title":"Learning world transition model for socially aware robot navigation","author":"cui","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9341519"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/70.704225"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460968"},{"key":"ref27","article-title":"Measuring the effects of autonomous mobile robot on pedestrian behavior","author":"oguchi","year":"0","journal-title":"2020 IJCAI-PRICAI Workshop on Neuro-Cognitive Modeling of Humans and Environments"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197497"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202312"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICIInfS.2013.6732028"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561703"},{"key":"ref8","article-title":"Decentralized structural-rnn for robot crowd navigation with deep reinforcement learning","author":"liu","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593871"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2013.05.007"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340705"},{"key":"ref1","article-title":"Distributed prioritized experience replay","author":"horgan","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref20","first-page":"1407","article-title":"Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures","author":"espeholt","year":"2018","journal-title":"International Conference on Machine Learning"},{"key":"ref22","first-page":"6252","article-title":"Towards optimally decentralized multi-robot collision avoidance via deep re-inforcement learning","author":"long","year":"0","journal-title":"2018 IEEE International Conference on Robotics and Automation (ICRA)"},{"key":"ref21","first-page":"1928","article-title":"Asynchronous methods for deep reinforcement learning","author":"mnih","year":"2016","journal-title":"International Conference on Machine Learning"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2974695"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553380"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.2009.0405"},{"key":"ref25","article-title":"Prioritized experience replay","author":"schaul","year":"2015","journal-title":"ArXiv Preprint"}],"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\/09812011.pdf?arnumber=9812011","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T19:07:23Z","timestamp":1667502443000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9812011\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/icra46639.2022.9812011","relation":{},"subject":[],"published":{"date-parts":[[2022,5,23]]}}}