{"id":"https://openalex.org/W7140444750","doi":"https://doi.org/10.1109/aixvr67263.2026.00075","title":"Floor Flattening of Image-Based 3D Reconstruction for Mobile Robots","display_name":"Floor Flattening of Image-Based 3D Reconstruction for Mobile Robots","publication_year":2026,"publication_date":"2026-01-26","ids":{"openalex":"https://openalex.org/W7140444750","doi":"https://doi.org/10.1109/aixvr67263.2026.00075"},"language":null,"primary_location":{"id":"doi:10.1109/aixvr67263.2026.00075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aixvr67263.2026.00075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)","raw_type":"proceedings-article"},"type":"article","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/A5111566709","display_name":"Suk Ku Sim","orcid":"https://orcid.org/0009-0009-3901-1253"},"institutions":[{"id":"https://openalex.org/I113825674","display_name":"Handong Global University","ror":"https://ror.org/00txhkt32","country_code":"KR","type":"education","lineage":["https://openalex.org/I113825674"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seonghwan Sim","raw_affiliation_strings":["School of Computer Science and Electrical Engineering, Handong Global University,Pohang,South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Electrical Engineering, Handong Global University,Pohang,South Korea","institution_ids":["https://openalex.org/I113825674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130680388","display_name":"Yeji Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I113825674","display_name":"Handong Global University","ror":"https://ror.org/00txhkt32","country_code":"KR","type":"education","lineage":["https://openalex.org/I113825674"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yeji Kim","raw_affiliation_strings":["School of Computer Science and Electrical Engineering, Handong Global University,Pohang,South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Electrical Engineering, Handong Global University,Pohang,South Korea","institution_ids":["https://openalex.org/I113825674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130644132","display_name":"Sung Soo Hwang","orcid":null},"institutions":[{"id":"https://openalex.org/I113825674","display_name":"Handong Global University","ror":"https://ror.org/00txhkt32","country_code":"KR","type":"education","lineage":["https://openalex.org/I113825674"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung Soo Hwang","raw_affiliation_strings":["School of Computer Science and Electrical Engineering, Handong Global University,Pohang,South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Electrical Engineering, Handong Global University,Pohang,South Korea","institution_ids":["https://openalex.org/I113825674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111566709"],"corresponding_institution_ids":["https://openalex.org/I113825674"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93787926,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"441","last_page":"446"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.2791000008583069,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.2791000008583069,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.2037999927997589,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.11060000211000443,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/flattening","display_name":"Flattening","score":0.6118000149726868},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.44929999113082886},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4205000102519989},{"id":"https://openalex.org/keywords/3d-reconstruction","display_name":"3D reconstruction","score":0.3846000134944916},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.33889999985694885},{"id":"https://openalex.org/keywords/grippers","display_name":"Grippers","score":0.2987000048160553}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6622999906539917},{"id":"https://openalex.org/C19444555","wikidata":"https://www.wikidata.org/wiki/Q212750","display_name":"Flattening","level":2,"score":0.6118000149726868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5953999757766724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4952000081539154},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.44929999113082886},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3172000050544739},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aixvr67263.2026.00075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aixvr67263.2026.00075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6194702386856079,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2085261163","https://openalex.org/W4281608743","https://openalex.org/W4385318467","https://openalex.org/W4391435390","https://openalex.org/W4400403028"],"related_works":[],"abstract_inverted_index":{"Training":[0],"robots":[1],"in":[2,104,130,138],"real-world":[3],"is":[4,34,59],"costly":[5],"and":[6,27,54,73,91,99,110,124,150],"time-consuming.":[7],"Consequently,":[8],"recent":[9],"research":[10],"has":[11],"increasingly":[12],"used":[13],"simulator-based":[14],"virtual":[15,40],"environments":[16],"for":[17,37,66],"robot":[18,156],"training.":[19],"3D":[20,29,106],"Gaussian":[21,107],"Splatting,":[22],"which":[23],"can":[24],"generate":[25],"fast":[26],"photorealistic":[28],"scenes":[30],"from":[31],"multi-view":[32],"images,":[33],"particularly":[35],"suitable":[36],"constructing":[38],"such":[39,51],"environments.":[41],"However,":[42],"due":[43],"to":[44,61,159],"the":[45,63,101,105,113,143,152,160],"inherent":[46],"characteristics":[47],"of":[48,85,154],"splats,":[49],"artifacts":[50],"as":[52],"floaters":[53],"noise":[55,149],"frequently":[56],"arise,":[57],"it":[58],"unsuitable":[60],"make":[62],"raw":[64],"representation":[65],"simulators":[67],"that":[68,127],"rely":[69],"on":[70],"physics":[71],"engines":[72],"collision":[74,125],"detection.":[75],"To":[76],"address":[77],"these":[78],"limitations,":[79],"we":[80,136],"propose":[81],"a":[82,139],"pipeline":[83],"composed":[84],"YOLO-based":[86],"floor":[87,102],"segmentation,":[88],"planar":[89],"estimation,":[90],"mesh":[92,145],"reconstruction.":[93],"The":[94],"proposed":[95],"method":[96],"reliably":[97],"identifies":[98],"flattens":[100],"region":[103],"Splatting":[108],"model":[109],"converts":[111],"only":[112],"non-floor":[114],"regions":[115],"into":[116],"meshes.":[117],"This":[118],"approach":[119],"effectively":[120],"reduces":[121],"surface":[122],"irregularities":[123],"errors":[126],"commonly":[128],"occur":[129],"conventional":[131],"gaussian-to-mesh":[132],"conversion":[133],"methods.":[134],"When":[135],"deployed":[137],"Unity-based":[140],"simulation":[141],"environment,":[142],"reconstructed":[144],"significantly":[146],"reduced":[147],"floor-related":[148],"improved":[151],"stability":[153],"mobile":[155],"navigation":[157],"compared":[158],"baseline.":[161]},"counts_by_year":[],"updated_date":"2026-03-28T06:11:35.319607","created_date":"2026-03-27T00:00:00"}
