{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T16:46:47Z","timestamp":1777654007651,"version":"3.51.4"},"reference-count":28,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100006769","name":"Russian Science Foundation","doi-asserted-by":"publisher","award":["20-71-10116"],"award-info":[{"award-number":["20-71-10116"]}],"id":[{"id":"10.13039\/501100006769","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3182803","type":"journal-article","created":{"date-parts":[[2022,6,13]],"date-time":"2022-06-13T20:37:15Z","timestamp":1655152635000},"page":"70447-70455","source":"Crossref","is-referenced-by-count":9,"title":["Hierarchical Landmark Policy Optimization for Visual Indoor Navigation"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4730-1543","authenticated-orcid":false,"given":"Aleksei","family":"Staroverov","sequence":"first","affiliation":[{"name":"Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9747-3837","authenticated-orcid":false,"given":"Aleksandr I.","family":"Panov","sequence":"additional","affiliation":[{"name":"Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/70.938381"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TSSC.1968.300136"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1613\/jair.2994"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-archives-XLII-2-W13-1709-2019"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2021.3083149"},{"key":"ref6","article-title":"AI2-thor: An interactive 3D environment for visual AI","author":"Kolve","year":"2019"},{"key":"ref7","article-title":"Minos: Multimodal indoor simulator for navigation in complex environments","author":"Savva","year":"2017"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00943"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00945"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2017.00081"},{"key":"ref11","article-title":"Joint 2D-3D-semantic data for indoor scene understanding","author":"Armeni","year":"2017"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.1998.712192"},{"key":"ref13","article-title":"Benchmarking classic and learned navigation in complex 3D environments","author":"Mishkin","year":"2019"},{"key":"ref14","article-title":"On evaluation of embodied navigation agents","author":"Anderson","year":"2018"},{"key":"ref15","article-title":"ObjectNav revisited: On evaluation of embodied agents navigating to objects","author":"Batra","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01581"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CIRA.1997.613851"},{"key":"ref18","article-title":"DD-PPO: Learning near-perfect pointgoal navigators from 2.5 billion frames","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Wijmans"},{"key":"ref19","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017"},{"key":"ref20","article-title":"How to train pointgoal navigation agents on a (sample and compute) budget","volume-title":"Proc. 21st Int. Conf. Auton. Agents Multiagent Syst.","author":"Wijmans"},{"key":"ref21","first-page":"4247","article-title":"Object goal navigation using goal-oriented semantic exploration","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Chaplot"},{"key":"ref22","first-page":"28336","article-title":"Landmark-guided subgoal generation in hierarchical reinforcement learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Kim"},{"key":"ref23","first-page":"26963","article-title":"Successor feature landmarks for long-horizon goal-conditioned reinforcement learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Hoang"},{"key":"ref24","article-title":"Objectnav revisited: On evaluation of embodied agents navigating to objects","author":"Batra","year":"2020"},{"key":"ref25","first-page":"17721","article-title":"Solov2: Dynamic and fast instance segmantation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Wang"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref27","article-title":"RedNet: Residual encoder\u2013decoder network for indoor RGB-D semantic segmentation","author":"Jiang","year":"2018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00027"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09795006.pdf?arnumber=9795006","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T02:52:49Z","timestamp":1706755969000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9795006\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3182803","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}