{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T14:01:52Z","timestamp":1785074512371,"version":"3.55.0"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Robotics and Autonomous Systems"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.robot.2026.105590","type":"journal-article","created":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T23:36:57Z","timestamp":1782171417000},"page":"105590","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Registering the 4D millimeter wave radar point clouds via Generalized Method of Moments"],"prefix":"10.1016","volume":"204","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-0045-9995","authenticated-orcid":false,"given":"Xingyi","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3905-0633","authenticated-orcid":false,"given":"Han","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8219-095X","authenticated-orcid":false,"given":"Ziliang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2623-8549","authenticated-orcid":false,"given":"Yukai","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8757-0679","authenticated-orcid":false,"given":"Weidong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"8","key":"10.1016\/j.robot.2026.105590_b1","doi-asserted-by":"crossref","first-page":"5124","DOI":"10.1109\/LRA.2023.3292574","article-title":"4D radar-based pose graph slam with ego-velocity pre-integration factor","volume":"8","author":"Li","year":"2023","journal-title":"IEEE Robotics Autom. Lett."},{"key":"10.1016\/j.robot.2026.105590_b2","series-title":"2023 IEEE International Conference on Robotics and Automation","first-page":"8333","article-title":"4Dradarslam: A 4d imaging radar slam system for large-scale environments based on pose graph optimization","author":"Zhang","year":"2023"},{"key":"10.1016\/j.robot.2026.105590_b3","article-title":"Radar4motion: Imu-free 4d radar odometry with robust dynamic filtering and rcs-weighted matching","author":"Kim","year":"2024","journal-title":"IEEE Trans. Intell. Veh."},{"key":"10.1016\/j.robot.2026.105590_b4","series-title":"2025 IEEE International Conference on Robotics and Automation","first-page":"6206","article-title":"Radar4voxmap: Accurate odometry from blurred radar observations","author":"Seok","year":"2025"},{"key":"10.1016\/j.robot.2026.105590_b5","series-title":"A comprehensive survey on point cloud registration","author":"Huang","year":"2021"},{"key":"10.1016\/j.robot.2026.105590_b6","doi-asserted-by":"crossref","unstructured":"P.J. Besl, N.D. McKay, Method for registration of 3-d shapes, in: Sensor Fusion IV: Control Paradigms and Data Structures, Vol. 1611, Spie, 1992, pp. 586\u2013606.","DOI":"10.1117\/12.57955"},{"key":"10.1016\/j.robot.2026.105590_b7","doi-asserted-by":"crossref","unstructured":"A. Segal, D. Haehnel, S. Thrun, Generalized-icp, in: Robotics: Science and Systems, Vol. 2, Seattle, WA, 2009, p. 435.","DOI":"10.15607\/RSS.2009.V.021"},{"key":"10.1016\/j.robot.2026.105590_b8","series-title":"Dicp: Doppler iterative closest point algorithm","author":"Hexsel","year":"2022"},{"issue":"2","key":"10.1016\/j.robot.2026.105590_b9","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1109\/TRO.2020.3033695","article-title":"Teaser: Fast and certifiable point cloud registration","volume":"37","author":"Yang","year":"2020","journal-title":"IEEE Trans. Robotics"},{"key":"10.1016\/j.robot.2026.105590_b10","series-title":"The Three-Dimensional Normal-Distributions Transform: an Efficient Representation for Registration, Surface Analysis, and Loop Detection","author":"Magnusson","year":"2009"},{"issue":"12","key":"10.1016\/j.robot.2026.105590_b11","doi-asserted-by":"crossref","first-page":"2262","DOI":"10.1109\/TPAMI.2010.46","article-title":"Point set registration: Coherent point drift","volume":"32","author":"Myronenko","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"8","key":"10.1016\/j.robot.2026.105590_b12","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1109\/TPAMI.2010.223","article-title":"Robust point set registration using gaussian mixture models","volume":"33","author":"Jian","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.robot.2026.105590_b13","series-title":"International Conference on Algorithmic Learning Theory","first-page":"13","article-title":"A hilbert space embedding for distributions","author":"Smola","year":"2007"},{"issue":"1","key":"10.1016\/j.robot.2026.105590_b14","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"Gretton","year":"2012","journal-title":"J. Mach. Learn. Res."},{"issue":"1\u20132","key":"10.1016\/j.robot.2026.105590_b15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000060","article-title":"Kernel mean embedding of distributions: A review and beyond","volume":"10","author":"Muandet","year":"2017","journal-title":"Found. Trends Mach. Learn."},{"key":"10.1016\/j.robot.2026.105590_b16","series-title":"2009 IEEE International Conference on Robotics and Automation","first-page":"3212","article-title":"Fast point feature histograms (fpfh) for 3d registration","author":"Rusu","year":"2009"},{"key":"10.1016\/j.robot.2026.105590_b17","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.cviu.2014.04.011","article-title":"Shot: Unique signatures of histograms for surface and texture description","volume":"125","author":"Salti","year":"2014","journal-title":"Comput. Vis. Image Underst."},{"key":"10.1016\/j.robot.2026.105590_b18","doi-asserted-by":"crossref","unstructured":"Y. Wang, J.M. Solomon, Deep closest point: Learning representations for point cloud registration, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2019, pp. 3523\u20133532.","DOI":"10.1109\/ICCV.2019.00362"},{"key":"10.1016\/j.robot.2026.105590_b19","doi-asserted-by":"crossref","unstructured":"Y. Aoki, H. Goforth, R.A. Srivatsan, S. Lucey, Pointnetlk: Robust & efficient point cloud registration using pointnet, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 7163\u20137172.","DOI":"10.1109\/CVPR.2019.00733"},{"key":"10.1016\/j.robot.2026.105590_b20","unstructured":"C.R. Qi, H. Su, K. Mo, L.J. Guibas, Pointnet: Deep learning on point sets for 3d classification and segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 652\u2013660."},{"key":"10.1016\/j.robot.2026.105590_b21","doi-asserted-by":"crossref","unstructured":"X. Li, J.K. Pontes, S. Lucey, Pointnetlk revisited, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 12763\u201312772.","DOI":"10.1109\/CVPR46437.2021.01257"},{"key":"10.1016\/j.robot.2026.105590_b22","first-page":"1029","article-title":"Large sample properties of generalized method of moments estimators","author":"Hansen","year":"1982","journal-title":"Econ.: J. Econ. Soc."},{"issue":"1","key":"10.1016\/j.robot.2026.105590_b23","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1137\/1019005","article-title":"Quasi-newton methods, motivation and theory","volume":"19","author":"Dennis","year":"1977","journal-title":"SIAM Rev."},{"issue":"3","key":"10.1016\/j.robot.2026.105590_b24","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/0009-2614(85)80574-1","article-title":"A broyden\u2014fletcher\u2014goldfarb\u2014shanno optimization procedure for molecular geometries","volume":"122","author":"Head","year":"1985","journal-title":"Chem. Phys. Lett."},{"key":"10.1016\/j.robot.2026.105590_b25","series-title":"16th International IEEE Conference on Intelligent Transportation Systems","first-page":"869","article-title":"Instantaneous ego-motion estimation using doppler radar","author":"Kellner","year":"2013"},{"key":"10.1016\/j.robot.2026.105590_b26","doi-asserted-by":"crossref","unstructured":"B. Curless, M. Levoy, A volumetric method for building complex models from range images, in: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, 1996, pp. 303\u2013312.","DOI":"10.1145\/237170.237269"},{"key":"10.1016\/j.robot.2026.105590_b27","series-title":"2023 IEEE 26th International Conference on Intelligent Transportation Systems","first-page":"4291","article-title":"Ntu4dradlm: 4d radar-centric multi-modal dataset for localization and mapping","author":"Zhang","year":"2023"},{"key":"10.1016\/j.robot.2026.105590_b28","series-title":"2011 IEEE International Conference on Robotics and Automation","first-page":"1","article-title":"3D is here: Point cloud library (pcl)","author":"Rusu","year":"2011"},{"key":"10.1016\/j.robot.2026.105590_b29","unstructured":"N. Nat, probreg: Python package for point cloud registration using probabilistic model. https:\/\/github.com\/neka-nat\/probreg."},{"key":"10.1016\/j.robot.2026.105590_b30","series-title":"2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"4802","article-title":"Scan context: Egocentric spatial descriptor for place recognition within 3D point cloud map","author":"Kim","year":"2018"},{"key":"10.1016\/j.robot.2026.105590_b31","series-title":"2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"4758","article-title":"Lego-loam: Lightweight and ground-optimized lidar odometry and mapping on variable terrain","author":"Shan","year":"2018"},{"key":"10.1016\/j.robot.2026.105590_b32","series-title":"2012 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"3354","article-title":"Are we ready for autonomous driving? The KITTI vision benchmark suite","author":"Geiger","year":"2012"},{"key":"10.1016\/j.robot.2026.105590_b33","series-title":"2012 IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"573","article-title":"A benchmark for the evaluation of rgb-d slam systems","author":"Sturm","year":"2012"},{"key":"10.1016\/j.robot.2026.105590_b34","series-title":"2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"7244","article-title":"A tutorial on quantitative trajectory evaluation for visual (-inertial) odometry","author":"Zhang","year":"2018"}],"container-title":["Robotics and Autonomous Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0921889026002629?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0921889026002629?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T13:28:05Z","timestamp":1785072485000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0921889026002629"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":34,"alternative-id":["S0921889026002629"],"URL":"https:\/\/doi.org\/10.1016\/j.robot.2026.105590","relation":{},"ISSN":["0921-8890"],"issn-type":[{"value":"0921-8890","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Registering the 4D millimeter wave radar point clouds via Generalized Method of Moments","name":"articletitle","label":"Article Title"},{"value":"Robotics and Autonomous Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.robot.2026.105590","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"105590"}}