{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T18:07:33Z","timestamp":1732039653152,"version":"3.28.0"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"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":[[2020,5]]},"DOI":"10.1109\/icra40945.2020.9196771","type":"proceedings-article","created":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T21:25:46Z","timestamp":1600205146000},"page":"9555-9562","source":"Crossref","is-referenced-by-count":5,"title":["Learned Sampling Distributions for Efficient Planning in Hybrid Geometric and Object-Level Representations"],"prefix":"10.1109","author":[{"given":"Katherine","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martina","family":"Stadler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas","family":"Roy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1177\/0278364911406761"},{"article-title":"Probabilistic roadmaps for robot path planning","year":"1998","author":"kavraki","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2005.I.015"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2008.4543787"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1177\/0278364912456444"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139620"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460730"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2901898"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2014.2302442"},{"key":"ref19","first-page":"20","article-title":"Teaching a randomized planner to plan with semantic fields","author":"baldwin","year":"2010","journal-title":"TAROS 2010"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref27","article-title":"The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale","author":"kuznetsova","year":"2018","journal-title":"arXiv preprint arXiv 1811 00982"},{"key":"ref3","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017","journal-title":"arXiv preprint arXiv 1704 04861"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917691110"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794344"},{"key":"ref8","article-title":"Deep spatial af- fordance hierarchy: Spatial knowledge representation for planning in large-scale environments","author":"pronobis","year":"2017","journal-title":"ICAPS 2017 Workshop on Planning and Robotics"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206392"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1618228114"},{"key":"ref9","first-page":"213","article-title":"Learning over subgoals for efficient navigation of structured, unknown environments","author":"stein","year":"2018","journal-title":"Conference on Robot Learning"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4613-3724-9_43"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2005.1570709"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4020-6528-6_9"},{"key":"ref21","first-page":"689","article-title":"Multimodal deep learning","author":"ngiam","year":"2011","journal-title":"Proceedings of the 28th International Conference on Machine Learning (ICML-11)"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-012-9321-0"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/MRA.2012.2205651","article-title":"The Open Motion Planning Library","volume":"19","author":"?ucan","year":"2012","journal-title":"IEEE Robotics & Automation Magazine"},{"journal-title":"TensorFlow Large-Scale Machine Learning on Heterogeneous Systems","year":"2015","author":"abadi","key":"ref26"},{"key":"ref25","first-page":"21","article-title":"SSD: Single shot multibox detector","author":"liu","year":"2016","journal-title":"European Conference on Computer Vision"}],"event":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2020,5,31]]},"location":"Paris, France","end":{"date-parts":[[2020,8,31]]}},"container-title":["2020 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9187508\/9196508\/09196771.pdf?arnumber=9196771","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:11:53Z","timestamp":1656375113000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9196771\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/icra40945.2020.9196771","relation":{},"subject":[],"published":{"date-parts":[[2020,5]]}}}