{"id":"https://openalex.org/W7133719262","doi":"https://doi.org/10.48550/arxiv.2603.03695","title":"TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory","display_name":"TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory","publication_year":2026,"publication_date":"2026-03-04","ids":{"openalex":"https://openalex.org/W7133719262","doi":"https://doi.org/10.48550/arxiv.2603.03695"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.03695","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128184482","display_name":"Minwoo Jung","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jung, Minwoo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128170533","display_name":"Dongjae Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Dongjae","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124897131","display_name":"Nived Chebrolu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chebrolu, Nived","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111153033","display_name":"Haedam Oh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oh, Haedam","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128161368","display_name":"Maurice Fallon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fallon, Maurice","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100740105","display_name":"Ayoung Kim","orcid":"https://orcid.org/0009-0007-7868-0498"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Ayoung","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5128184482"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.8950999975204468,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.8950999975204468,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.056299999356269836,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.007199999876320362,"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/point-cloud","display_name":"Point cloud","score":0.7932999730110168},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6527000069618225},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5902000069618225},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5112000107765198},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4675999879837036},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.46399998664855957},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.3817000091075897},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.36399999260902405},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.36000001430511475}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7932999730110168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6600000262260437},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6527000069618225},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5902000069618225},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5112000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4887000024318695},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.46399998664855957},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3962000012397766},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.3817000091075897},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36899998784065247},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.36399999260902405},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C64331007","wikidata":"https://www.wikidata.org/wiki/Q831672","display_name":"Spanning tree","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.314300000667572},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.27720001339912415},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.03695","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.03695","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03695","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.03695","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"localization":[1,59,87,171,198],"is":[2,32],"essential":[3],"for":[4,260],"sustainable":[5],"forest":[6],"management,":[7],"as":[8,94],"it":[9],"allows":[10],"robots":[11],"or":[12],"sensor":[13],"systems":[14],"to":[15,74,101,148,206],"revisit":[16],"and":[17,61,76,115,144,163,168,190,241,245],"monitor":[18],"the":[19,99,103,117,256],"status":[20],"of":[21,119,233,238,258],"individual":[22],"trees":[23],"over":[24],"long":[25],"periods.":[26],"In":[27],"modern":[28],"forestry,":[29],"this":[30],"management":[31],"structured":[33],"around":[34],"Digital":[35],"Forest":[36],"Inventories":[37],"(DFIs),":[38],"which":[39],"encode":[40],"stems":[41],"using":[42,235],"compact":[43],"geometric":[44],"attributes":[45],"rather":[46],"than":[47],"raw":[48,104],"data.":[49,179],"Despite":[50],"their":[51],"central":[52],"role,":[53],"DFIs":[54,93],"have":[55],"been":[56],"overlooked":[57],"in":[58,111,185,213],"research,":[60],"most":[62],"methods":[63],"still":[64],"rely":[65,249],"on":[66,92,174,181,250],"dense":[67,175],"gigabyte-sized":[68],"point":[69,105,177,251],"clouds":[70],"that":[71,89,133,194,248],"are":[72],"costly":[73],"store":[75],"maintain.":[77],"To":[78],"improve":[79],"upon":[80],"this,":[81],"we":[82],"propose":[83],"TreeLoc++,":[84],"a":[85,95,129,153,222],"global":[86],"framework":[88],"operates":[90],"directly":[91],"discriminative":[96],"representation,":[97],"eliminating":[98],"need":[100],"use":[102],"clouds.":[106],"TreeLoc++":[107,195,259],"reduces":[108],"false":[109],"matches":[110],"structurally":[112],"ambiguous":[113],"forests":[114,186],"improves":[116],"reliability":[118],"full":[120],"6-DoF":[121],"pose":[122,166],"estimation.":[123],"It":[124],"augments":[125],"coarse":[126],"retrieval":[127],"with":[128,199],"pairwise":[130],"distance":[131],"histogram":[132],"encodes":[134],"local":[135],"tree-layout":[136],"context,":[137],"subsequently":[138],"refining":[139],"candidates":[140],"via":[141],"DBH-based":[142],"filtering":[143],"yaw-consistent":[145],"inlier":[146],"selection":[147],"further":[149,203],"reduce":[150],"mismatches.":[151],"Furthermore,":[152],"constrained":[154],"optimization":[155],"leveraging":[156],"tree":[157],"geometry":[158],"jointly":[159],"estimates":[160],"roll,":[161],"pitch,":[162],"height,":[164],"enhancing":[165],"stability":[167],"enabling":[169],"accurate":[170],"without":[172],"reliance":[173],"3D":[176],"cloud":[178,252],"Evaluations":[180],"27":[182],"sequences":[183],"recorded":[184,212],"across":[187],"three":[188],"datasets":[189],"four":[191],"countries":[192],"show":[193],"achieves":[196],"precise":[197],"centimeter-level":[200],"accuracy.":[201],"We":[202],"demonstrate":[204],"robustness":[205],"long-term":[207,261],"change":[208],"by":[209],"localizing":[210],"data":[211,240],"2025":[214],"against":[215],"inventories":[216],"built":[217],"from":[218],"2023":[219],"data,":[220],"spanning":[221,230],"two-year":[223],"interval.":[224],"The":[225],"system":[226],"represents":[227],"15":[228],"sessions":[229],"7.98":[231],"km":[232],"trajectories":[234],"only":[236],"250KB":[237],"map":[239],"outperforms":[242],"both":[243],"hand-crafted":[244],"learning-based":[246],"baselines":[247],"maps.":[253],"This":[254],"demonstrates":[255],"scalability":[257],"deployment.":[262]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-06T00:00:00"}
