{"id":"https://openalex.org/W2561199234","doi":"https://doi.org/10.1109/iros.2016.7759112","title":"Active exploration using Gaussian Random Fields and Gaussian Process Implicit Surfaces","display_name":"Active exploration using Gaussian Random Fields and Gaussian Process Implicit Surfaces","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2561199234","doi":"https://doi.org/10.1109/iros.2016.7759112","mag":"2561199234"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2016.7759112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1802.04642","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086561515","display_name":"Sergio Caccamo","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Sergio Caccamo","raw_affiliation_strings":["Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE"],"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015300584","display_name":"Yasemin Bekiroglu","orcid":"https://orcid.org/0000-0002-2597-6013"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Yasemin Bekiroglu","raw_affiliation_strings":["Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE"],"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022800415","display_name":"Carl Henrik Ek","orcid":"https://orcid.org/0000-0003-1302-6309"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Carl Henrik Ek","raw_affiliation_strings":["Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE"],"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023792180","display_name":"Danica Kragi\u0107","orcid":"https://orcid.org/0000-0003-2965-2953"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Danica Kragic","raw_affiliation_strings":["Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE"],"affiliations":[{"raw_affiliation_string":"Computer Vision and Active Perception Lab., Royal Institute of Technology (KTH), Stockholm, SE","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5086561515"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":3.5495,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.94047471,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"582","last_page":"589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9230999946594238,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/gaussian-process","display_name":"Gaussian process","score":0.7307077646255493},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6687670350074768},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6400583982467651},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6366260647773743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6156848669052124},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5892734527587891},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5842424631118774},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.5725773572921753},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5424292087554932},{"id":"https://openalex.org/keywords/random-field","display_name":"Random field","score":0.537988007068634},{"id":"https://openalex.org/keywords/active-perception","display_name":"Active perception","score":0.49454161524772644},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.48556897044181824},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4425595700740814},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.44163233041763306},{"id":"https://openalex.org/keywords/gaussian-random-field","display_name":"Gaussian random field","score":0.4410698711872101},{"id":"https://openalex.org/keywords/tactile-sensor","display_name":"Tactile sensor","score":0.42535439133644104},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4244832992553711},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18987935781478882},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16406497359275818},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09228751063346863},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07813987135887146}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.7307077646255493},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6687670350074768},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6400583982467651},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6366260647773743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6156848669052124},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5892734527587891},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5842424631118774},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5725773572921753},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5424292087554932},{"id":"https://openalex.org/C130402806","wikidata":"https://www.wikidata.org/wiki/Q5361768","display_name":"Random field","level":2,"score":0.537988007068634},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.49454161524772644},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.48556897044181824},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4425595700740814},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.44163233041763306},{"id":"https://openalex.org/C51267290","wikidata":"https://www.wikidata.org/wiki/Q5527848","display_name":"Gaussian random field","level":4,"score":0.4410698711872101},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.42535439133644104},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4244832992553711},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18987935781478882},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16406497359275818},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09228751063346863},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07813987135887146},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iros.2016.7759112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1802.04642","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.04642","pdf_url":"https://arxiv.org/pdf/1802.04642","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/25c9960d-11d9-4527-848a-e88b0fa45780","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/25c9960d-11d9-4527-848a-e88b0fa45780","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Caccamo, S, Bekiroglu, Y, Ek, C H & Kragic, D 2018, 'Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces', arXiv. https://doi.org/10.1109/IROS.2016.7759112","raw_type":"article"},{"id":"pmh:oai:research.chalmers.se:518847","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/518847","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1802.04642","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1802.04642","pdf_url":"https://arxiv.org/pdf/1802.04642","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W31424620","https://openalex.org/W91269655","https://openalex.org/W1524341542","https://openalex.org/W1570448822","https://openalex.org/W1584218047","https://openalex.org/W1746819321","https://openalex.org/W1775013730","https://openalex.org/W1964742754","https://openalex.org/W1969090956","https://openalex.org/W1985639699","https://openalex.org/W2050595634","https://openalex.org/W2082927964","https://openalex.org/W2091271588","https://openalex.org/W2099953968","https://openalex.org/W2107153006","https://openalex.org/W2115846099","https://openalex.org/W2119104235","https://openalex.org/W2124825847","https://openalex.org/W2130684472","https://openalex.org/W2137956165","https://openalex.org/W2139230981","https://openalex.org/W2147751396","https://openalex.org/W2155770057","https://openalex.org/W2156067790","https://openalex.org/W2156583822","https://openalex.org/W2158483689","https://openalex.org/W2161674001","https://openalex.org/W2168270181","https://openalex.org/W2244686166","https://openalex.org/W2495887577","https://openalex.org/W2515158851","https://openalex.org/W2963654998","https://openalex.org/W2998100778","https://openalex.org/W3023790412","https://openalex.org/W4211049957","https://openalex.org/W4252017042","https://openalex.org/W6601271567","https://openalex.org/W6603706610","https://openalex.org/W6687839724","https://openalex.org/W6726168421","https://openalex.org/W6991122698"],"related_works":["https://openalex.org/W3101730079","https://openalex.org/W4285599464","https://openalex.org/W2949623712","https://openalex.org/W4301970141","https://openalex.org/W1901925154","https://openalex.org/W2262012800","https://openalex.org/W3083204305","https://openalex.org/W2090206927","https://openalex.org/W2013997342","https://openalex.org/W2001600790"],"abstract_inverted_index":{"In":[0],"this":[1],"work":[2],"we":[3],"study":[4],"the":[5,16,101],"problem":[6],"of":[7,15,58,60],"exploring":[8],"surfaces":[9],"and":[10,33,40,89,107],"building":[11],"compact":[12],"3D":[13],"representations":[14],"environment":[17],"surrounding":[18],"a":[19,55,68,81,84],"robot":[20],"through":[21],"active":[22],"perception.":[23],"We":[24,75,95],"propose":[25],"an":[26],"online":[27,102],"probabilistic":[28],"framework":[29,103],"that":[30],"merges":[31],"visual":[32],"tactile":[34,73],"measurements":[35],"using":[36,80],"Gaussian":[37,41],"Random":[38],"Field":[39],"Process":[42],"Implicit":[43],"Surfaces.":[44],"The":[45],"system":[46],"investigates":[47],"incomplete":[48],"point":[49],"clouds":[50],"in":[51],"order":[52],"to":[53,99],"find":[54],"small":[56],"set":[57],"regions":[59],"interest":[61],"which":[62],"are":[63],"then":[64,96],"physically":[65],"explored":[66],"with":[67,72],"robotic":[69,87],"arm":[70,88],"equipped":[71],"sensors.":[74],"show":[76],"experimental":[77],"results":[78],"obtained":[79],"PrimeSense":[82],"camera,":[83],"Kinova":[85],"Jaco2":[86],"Optoforce":[90],"sensors":[91],"on":[92],"different":[93],"scenarios.":[94],"demostrate":[97],"how":[98],"use":[100],"for":[104],"object":[105],"detection":[106],"terrain":[108],"classification.":[109]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2020-11-23T00:00:00"}
