{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T10:04:09Z","timestamp":1766138649034,"version":"3.37.3"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Shenzhen Portion of Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone","award":["HZQB-KCZYB-20200089"],"award-info":[{"award-number":["HZQB-KCZYB-20200089"]}]},{"name":"RGC","award":["14207119"],"award-info":[{"award-number":["14207119"]}]},{"name":"InnoHK of the Government of the Hong Kong Special Administrative Region via the Hong Kong Centre for Logistics Robotics"},{"name":"CUHK T Sone Robotics Institute"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1109\/lra.2024.3385609","type":"journal-article","created":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T18:49:43Z","timestamp":1712342983000},"page":"4934-4941","source":"Crossref","is-referenced-by-count":7,"title":["Uncertainty-Aware Suction Grasping for Cluttered Scenes"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5657-7325","authenticated-orcid":false,"given":"Rui","family":"Cao","sequence":"first","affiliation":[{"name":"Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5956-7350","authenticated-orcid":false,"given":"Biqi","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8473-5378","authenticated-orcid":false,"given":"Yichuan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5238-593X","authenticated-orcid":false,"given":"Chi-Wing","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3055-5034","authenticated-orcid":false,"given":"Pheng-Ann","family":"Heng","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3625-6679","authenticated-orcid":false,"given":"Yun-Hui","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811646"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01197"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3115406"},{"key":"ref4","first-page":"6358","article-title":"Reinforcement learning for picking cluttered general objects with dense object descriptors","volume-title":"Proc. Int. Conf. Robot. Automat.","author":"Giang","year":"2022"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00319"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00182"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2016.XII.036"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ROBIO55434.2022.10011780"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.5555\/3045390.3045502"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68792-6_51"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01414"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2022.806898"},{"key":"ref13","first-page":"5580","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Kendall","year":"2017"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3149026"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967816"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460887"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8463191"},{"key":"ref18","first-page":"652","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Qi","year":"2017"},{"key":"ref19","first-page":"5105","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Qi","year":"2017"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58545-7_35"},{"key":"ref21","first-page":"8216","article-title":"Mask3D for 3D semantic instance segmentation","volume-title":"Proc. Int. Conf. Robot. Automat.","author":"Schult","year":"2023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IROS47612.2022.9981866"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00651"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811599"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CASE49439.2021.9551603"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01455"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00346"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01194"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2021.3060341"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8461044"},{"article-title":"Open3D: A modern library for 3D data processing","year":"2018","author":"Zhou","key":"ref32"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9341056"},{"key":"ref34","first-page":"2595","article-title":"Parallelized stochastic gradient descent","volume-title":"Proc. Neural Inf. Process. Syst.","volume":"23","author":"Zinkevich","year":"2010"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7083369\/10504377\/10493125.pdf?arnumber=10493125","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T19:31:10Z","timestamp":1734982270000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10493125\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6]]},"references-count":34,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/lra.2024.3385609","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"type":"electronic","value":"2377-3766"},{"type":"electronic","value":"2377-3774"}],"subject":[],"published":{"date-parts":[[2024,6]]}}}