{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:27:11Z","timestamp":1775744831354,"version":"3.50.1"},"reference-count":27,"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\/icra48506.2021.9561462","type":"proceedings-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:28:35Z","timestamp":1634689715000},"page":"6057-6063","source":"Crossref","is-referenced-by-count":69,"title":["DWA-RL: Dynamically Feasible Deep Reinforcement Learning Policy for Robot Navigation among Mobile Obstacles"],"prefix":"10.1109","author":[{"given":"Utsav","family":"Patel","sequence":"first","affiliation":[]},{"given":"Nithish K Sanjeev","family":"Kumar","sequence":"additional","affiliation":[]},{"given":"Adarsh Jagan","family":"Sathyamoorthy","sequence":"additional","affiliation":[]},{"given":"Dinesh","family":"Manocha","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TSSC.1968.300136"},{"key":"ref11","article-title":"Rapidly-exploring random trees: A new tool for path planning","author":"lavalle","year":"1998","journal-title":"Tech Rep"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12328"},{"key":"ref13","first-page":"1986","article-title":"Dynamic window based approach to mobile robot motion control in the presence of moving obstacles","author":"seder","year":"2007"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2010.2058531"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2019.05.003"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.1996.511023"},{"key":"ref17","article-title":"Towards monocular vision based obstacle avoidance through deep reinforcement learning","author":"xie","year":"2017","journal-title":"CoRR"},{"key":"ref18","article-title":"End-to-end training of deep visuomotor policies","author":"levine","year":"2015","journal-title":"CoRR"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCE.2018.8326229"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8461113"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref3","article-title":"Collision avoidance in pedestrian-rich environments with deep reinforcement learning","author":"everett","year":"2019"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/100.580977"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.1991.131747"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794386"},{"key":"ref7","first-page":"1038","article-title":"Balancing multiple sources of reward in reinforcement learning","author":"shelton","year":"2000","journal-title":"Proceedings of the 13th International Conference on Neural Information Processing Systems"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197379"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/BF01386390"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/583"},{"key":"ref20","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":"CoRR"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593871"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989037"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202312"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460968"},{"key":"ref26","article-title":"Dynamically Feasible Deep Reinforcement Learning Policy for Robot Navigation in Dense Mobile Crowds","author":"patel","year":"2020"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2996593"}],"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\/09561462.pdf?arnumber=9561462","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:47:12Z","timestamp":1652197632000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9561462\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,30]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/icra48506.2021.9561462","relation":{},"subject":[],"published":{"date-parts":[[2021,5,30]]}}}