{"id":"https://openalex.org/W3170528657","doi":"https://doi.org/10.1109/icra48506.2021.9562044","title":"Markov Localisation using Heatmap Regression and Deep Convolutional Odometry","display_name":"Markov Localisation using Heatmap Regression and Deep Convolutional Odometry","publication_year":2021,"publication_date":"2021-05-30","ids":{"openalex":"https://openalex.org/W3170528657","doi":"https://doi.org/10.1109/icra48506.2021.9562044","mag":"3170528657"},"language":"en","primary_location":{"id":"doi:10.1109/icra48506.2021.9562044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9562044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2106.00371","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033644268","display_name":"Oscar M\u00e9ndez","orcid":"https://orcid.org/0000-0003-4904-4349"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Oscar Mendez","raw_affiliation_strings":["University of Surrey,Centre for Vision Speech and Signal Processing,Guildford,UK","University of Surrey,Centre for Vision, Speech and Signal Processing,Guildford,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision Speech and Signal Processing,Guildford,UK","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"University of Surrey,Centre for Vision, Speech and Signal Processing,Guildford,UK","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091184063","display_name":"Simon Hadfield","orcid":"https://orcid.org/0000-0001-8637-5054"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon Hadfield","raw_affiliation_strings":["University of Surrey,Centre for Vision Speech and Signal Processing,Guildford,UK","University of Surrey,Centre for Vision, Speech and Signal Processing,Guildford,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision Speech and Signal Processing,Guildford,UK","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"University of Surrey,Centre for Vision, Speech and Signal Processing,Guildford,UK","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044490167","display_name":"Richard Bowden","orcid":"https://orcid.org/0000-0003-3285-8020"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Richard Bowden","raw_affiliation_strings":["University of Surrey,Centre for Vision Speech and Signal Processing,Guildford,UK","University of Surrey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,Centre for Vision Speech and Signal Processing,Guildford,UK","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"University of Surrey","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06887725,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"95","issue":null,"first_page":"9638","last_page":"9644"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9986000061035156,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9962000250816345,"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/computer-science","display_name":"Computer science","score":0.8126260638237},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7368742227554321},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6331713199615479},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6214989423751831},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6131243705749512},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.46108171343803406},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.45945578813552856},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45282089710235596},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4490542709827423},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3914116322994232},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3845331072807312},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.08732044696807861},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08537611365318298}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8126260638237},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7368742227554321},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6331713199615479},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6214989423751831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6131243705749512},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.46108171343803406},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.45945578813552856},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45282089710235596},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4490542709827423},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3914116322994232},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3845331072807312},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.08732044696807861},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08537611365318298},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icra48506.2021.9562044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9562044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2106.00371","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.00371","pdf_url":"https://arxiv.org/pdf/2106.00371","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3170528657","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2106.00371","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2106.00371","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2106.00371","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2106.00371","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.00371","pdf_url":"https://arxiv.org/pdf/2106.00371","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3170528657.pdf","grobid_xml":"https://content.openalex.org/works/W3170528657.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W73143588","https://openalex.org/W107715831","https://openalex.org/W1516326277","https://openalex.org/W1577509784","https://openalex.org/W2021851106","https://openalex.org/W2105303354","https://openalex.org/W2131865378","https://openalex.org/W2169033759","https://openalex.org/W2194775991","https://openalex.org/W2200124539","https://openalex.org/W2201290997","https://openalex.org/W2567328166","https://openalex.org/W2584731199","https://openalex.org/W2605111497","https://openalex.org/W2767756217","https://openalex.org/W2771385090","https://openalex.org/W2772641132","https://openalex.org/W2795645133","https://openalex.org/W2798483995","https://openalex.org/W2922243907","https://openalex.org/W2962689474","https://openalex.org/W2963024893","https://openalex.org/W3035056458","https://openalex.org/W6603031904","https://openalex.org/W6604329173","https://openalex.org/W6679875354"],"related_works":["https://openalex.org/W3019462385","https://openalex.org/W3034822742","https://openalex.org/W3011943395","https://openalex.org/W2786877562","https://openalex.org/W3204032613","https://openalex.org/W3113341215","https://openalex.org/W2967296738","https://openalex.org/W3081487332","https://openalex.org/W3159708224","https://openalex.org/W3035678286","https://openalex.org/W2909990436","https://openalex.org/W3162754475","https://openalex.org/W3144571612","https://openalex.org/W2213503169","https://openalex.org/W3018359716","https://openalex.org/W3009736278","https://openalex.org/W3010364879","https://openalex.org/W3197033868","https://openalex.org/W3037148033","https://openalex.org/W3161889052"],"abstract_inverted_index":{"In":[0,202],"the":[1,36,62,82,96,124,129,178,182,196,228],"context":[2],"of":[3,64,88,131,195,198,257],"self-driving":[4],"vehicles":[5],"there":[6,105],"is":[7,29,106,117,255],"strong":[8],"competition":[9],"between":[10,110],"approaches":[11,69,142],"based":[12,68,141,200],"on":[13,177,227],"visual":[14],"localisation":[15,53,76,83,210,224,242,267],"and":[16,33,42,112,150,191,243],"Light":[17],"Detection":[18],"And":[19],"Ranging":[20],"(LiDAR).":[21],"While":[22],"LiDAR":[23],"provides":[24],"important":[25],"depth":[26],"information,":[27],"it":[28,116],"sparse":[30],"in":[31,45,61,165],"resolution":[32],"expensive.":[34],"On":[35],"other":[37],"hand,":[38],"cameras":[39],"are":[40],"low-cost":[41],"recent":[43],"developments":[44],"deep":[46,166,216],"learning":[47,67,167,217],"mean":[48],"they":[49],"can":[50,70,213,239],"provide":[51],"high":[52],"performance.":[54],"However,":[55,155],"several":[56],"fundamental":[57],"problems":[58,160],"remain,":[59],"particularly":[60],"domain":[63],"uncertainty,":[65],"where":[66],"be":[71,174],"notoriously":[72],"over-confident.Markov,":[73],"or":[74],"grid-based,":[75],"was":[77],"an":[78],"early":[79],"solution":[80],"to":[81,91,119,173,185],"problem":[84],"but":[85],"fell":[86],"out":[87],"favour":[89],"due":[90],"its":[92,158],"computational":[93],"complexity.":[94],"Representing":[95],"likelihood":[97,126,135,171,245],"field":[98],"as":[99,263,265],"a":[100,107,134,207,221,232,248],"grid":[101,140,199],"(or":[102],"volume)":[103],"means":[104],"trade":[108],"off":[109],"accuracy":[111],"memory":[113],"size.":[114],"Furthermore,":[115],"necessary":[118,184],"perform":[120,187,240],"expensive":[121],"convolutions":[122,190],"across":[123],"entire":[125],"volume.":[127],"Despite":[128],"benefit":[130],"simultaneously":[132],"maintaining":[133],"for":[136],"all":[137],"possible":[138],"locations,":[139],"were":[143],"superseded":[144],"by":[145],"more":[146],"efficient":[147],"particle":[148,162],"filters":[149],"Monte":[151],"Carlo":[152],"sampling":[153],"(MCL).":[154],"MCL":[156],"introduces":[157],"own":[159],"e.g.":[161],"deprivation.Recent":[163],"advances":[164],"hardware":[168,183],"allow":[169],"large":[170],"volumes":[172],"stored":[175],"directly":[176,226],"GPU,":[179,229],"along":[180],"with":[181],"efficiently":[186],"GPU-bound":[188],"3D":[189],"this":[192,203],"obviates":[193],"many":[194],"disadvantages":[197],"methods.":[201],"work,":[204],"we":[205,230],"present":[206],"novel":[208],"CNN-based":[209],"approach":[211,225,254],"that":[212,238],"leverage":[214],"modern":[215],"hardware.":[218],"By":[219],"implementing":[220],"grid-based":[222],"Markov":[223],"create":[231],"hybrid":[233],"Convolutional":[234],"Neural":[235],"Network":[236],"(CNN)":[237],"image-based":[241],"odometry-based":[244],"propagation":[246],"within":[247],"single":[249],"neural":[250],"network.":[251],"The":[252],"resulting":[253],"capable":[256],"outperforming":[258],"direct":[259],"pose":[260],"regression":[261],"methods":[262],"well":[264],"state-of-the-art":[266],"systems.":[268]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
