{"id":"https://openalex.org/W4416748488","doi":"https://doi.org/10.1109/iros60139.2025.11246456","title":"A Novel LiDAR Odometry Based on Surface Distributed Point Feature with Dual Feature Fusion","display_name":"A Novel LiDAR Odometry Based on Surface Distributed Point Feature with Dual Feature Fusion","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416748488","doi":"https://doi.org/10.1109/iros60139.2025.11246456"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11246456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101589727","display_name":"Jianjie Li","orcid":"https://orcid.org/0009-0009-6605-4830"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianjie Li","raw_affiliation_strings":["Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055132525","display_name":"Peiyu Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peiyu Guan","raw_affiliation_strings":["Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069171230","display_name":"Xurong Gong","orcid":"https://orcid.org/0009-0001-9017-1342"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xurong Gong","raw_affiliation_strings":["Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100745770","display_name":"Zhicheng Liu","orcid":"https://orcid.org/0000-0002-6278-1813"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhicheng Liu","raw_affiliation_strings":["Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101498614","display_name":"Zhiqiang Cao","orcid":"https://orcid.org/0000-0001-8578-5385"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Cao","raw_affiliation_strings":["Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3444","last_page":"3451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9312999844551086,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9312999844551086,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.019200000911951065,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.007300000172108412,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6528000235557556},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.6504999995231628},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.614300012588501},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5899999737739563},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5794000029563904},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4690000116825104},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4690000116825104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4165000021457672},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.38179999589920044}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7197999954223633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6837999820709229},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6528000235557556},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.6504999995231628},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.614300012588501},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5899999737739563},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5853000283241272},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5794000029563904},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.32989999651908875},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3280999958515167},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.31949999928474426},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.272599995136261},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C126795593","wikidata":"https://www.wikidata.org/wiki/Q7333813","display_name":"Rigid transformation","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.26669999957084656},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11246456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1567242735","https://openalex.org/W2080823437","https://openalex.org/W2131439959","https://openalex.org/W2150066425","https://openalex.org/W2162995444","https://openalex.org/W2296228853","https://openalex.org/W2766213449","https://openalex.org/W2909908358","https://openalex.org/W2963600667","https://openalex.org/W2981566147","https://openalex.org/W3003991701","https://openalex.org/W3007240855","https://openalex.org/W3127368595","https://openalex.org/W3131459917","https://openalex.org/W3203597819","https://openalex.org/W3205339211","https://openalex.org/W3206395965","https://openalex.org/W4205574455","https://openalex.org/W4205709873","https://openalex.org/W4213231647","https://openalex.org/W4249866455","https://openalex.org/W4285177584","https://openalex.org/W4285203935","https://openalex.org/W4285295417","https://openalex.org/W4313306324","https://openalex.org/W4382365531","https://openalex.org/W4400877877","https://openalex.org/W4405778951","https://openalex.org/W4405785372","https://openalex.org/W4405787438"],"related_works":[],"abstract_inverted_index":{"LiDAR":[0,8,87],"odometry":[1,88],"has":[2],"gained":[3],"popularity":[4],"due":[5],"to":[6,15,52,107,137,198],"the":[7,23,31,39,45,102,123,139,148,152,163,173,182,212,215],"sensor\u2019s":[9],"accurate":[10,200],"depth":[11],"measurement":[12],"and":[13,62,65,68,111,117,126,181,191,207],"robustness":[14],"varying":[16],"illumination":[17],"conditions.":[18],"The":[19,178],"feature-based":[20],"methods":[21,49],"achieve":[22,199],"advantage":[24],"of":[25,47,175,214],"efficiency":[26],"through":[27,133],"feature":[28,96,99,104,115,135,180],"extraction,":[29],"while":[30],"distribution-based":[32],"ones":[33],"attain":[34],"better":[35],"accuracy":[36,174],"by":[37],"modeling":[38],"point":[40,94],"cloud":[41],"as":[42,147],"distributions.":[43],"Combining":[44],"strengths":[46],"both":[48,188],"is":[50,105,167],"anticipated":[51],"yield":[53],"superior":[54],"performance.":[55],"However,":[56],"existing":[57],"combination":[58],"schemes":[59],"typically":[60],"extract":[61],"process":[63],"features":[64,110,128],"distributions":[66],"separately,":[67],"such":[69],"a":[70,85,161],"loosely":[71],"integrated":[72,132],"approach":[73],"cannot":[74],"fully":[75],"leverage":[76],"their":[77],"complementarity.":[78],"To":[79],"address":[80],"this":[81,121],"problem,":[82],"we":[83],"propose":[84],"novel":[86],"method":[89],"based":[90],"on":[91,204],"surface":[92],"distributed":[93],"(SDP)":[95],"with":[97],"dual":[98,134],"fusion.":[100],"Specifically,":[101],"SDP":[103,179],"introduced":[106],"tightly":[108],"integrate":[109],"distributions,":[112],"facilitating":[113],"efficient":[114],"association":[116],"map":[118],"maintenance.":[119],"On":[120],"basis,":[122],"associated":[124,142,154],"source":[125],"target":[127],"are":[129,185,195],"then":[130],"effectively":[131],"fusion":[136],"form":[138],"dual-fusion":[140],"(DF)":[141],"plane.":[143],"This":[144],"plane":[145,155],"serves":[146],"basis":[149],"for":[150,157],"constructing":[151],"point-to-DF":[153],"constraint":[156,184],"pose":[158,176,201],"optimization.":[159],"As":[160],"result,":[162],"local":[164],"planar":[165],"structure":[166],"more":[168],"accurately":[169],"reflected,":[170],"thereby":[171],"enhancing":[172],"estimation.":[177,202],"resultant":[183],"employed":[186],"in":[187],"scan-to-map":[189],"matching":[190],"fixed-lag":[192],"smoothing,":[193],"which":[194],"hierarchically":[196],"organized":[197],"Experiments":[203],"KITTI":[205],"dataset":[206,210],"large-scale":[208],"KITTI-360":[209],"demonstrate":[211],"effectiveness":[213],"proposed":[216],"method.":[217]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-28T00:00:00"}