{"id":"https://openalex.org/W4313027061","doi":"https://doi.org/10.1109/iros47612.2022.9982113","title":"Adaptive Sampling Site Selection for Robotic Exploration in Unknown Environments","display_name":"Adaptive Sampling Site Selection for Robotic Exploration in Unknown Environments","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W4313027061","doi":"https://doi.org/10.1109/iros47612.2022.9982113"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9982113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9982113","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5023184269","display_name":"Pranay Thangeda","orcid":"https://orcid.org/0000-0002-0680-6334"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pranay Thangeda","raw_affiliation_strings":["University of Illinois Urbana-Champaign,Coordinated Science Laboratory,Department of Aerospace Engineering,Urbana,USA","Department of Aerospace Engineering, Coordinated Science Laboratory, University of Illinois Urbana-Champaign, Urbana, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign,Coordinated Science Laboratory,Department of Aerospace Engineering,Urbana,USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Department of Aerospace Engineering, Coordinated Science Laboratory, University of Illinois Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070897457","display_name":"Melkior Ornik","orcid":"https://orcid.org/0000-0002-8510-8787"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Melkior Ornik","raw_affiliation_strings":["University of Illinois Urbana-Champaign,Coordinated Science Laboratory,Department of Aerospace Engineering,Urbana,USA","Department of Aerospace Engineering, Coordinated Science Laboratory, University of Illinois Urbana-Champaign, Urbana, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign,Coordinated Science Laboratory,Department of Aerospace Engineering,Urbana,USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Department of Aerospace Engineering, Coordinated Science Laboratory, University of Illinois Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8567,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69211618,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4120","last_page":"4125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12288","display_name":"Optimization and Search Problems","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12288","display_name":"Optimization and Search Problems","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998000264167786,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7820249199867249},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7568840384483337},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.7523314952850342},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.7344076037406921},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7289005517959595},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5348699688911438},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.5027461051940918},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5005180835723877},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.5003325939178467},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.49068009853363037},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4454082250595093},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4449785649776459},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43642663955688477},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.38902437686920166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38378655910491943},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3723728060722351},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34660956263542175},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.1964704990386963},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16752353310585022},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11001637578010559},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.0834178626537323}],"concepts":[{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7820249199867249},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7568840384483337},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.7523314952850342},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.7344076037406921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7289005517959595},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5348699688911438},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5027461051940918},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5005180835723877},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.5003325939178467},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.49068009853363037},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4454082250595093},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4449785649776459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43642663955688477},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.38902437686920166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38378655910491943},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3723728060722351},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34660956263542175},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.1964704990386963},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16752353310585022},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11001637578010559},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0834178626537323},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9982113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9982113","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G1351725428","display_name":null,"funder_award_id":"80NSSC21K1030","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"}],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1980516134","https://openalex.org/W2047987837","https://openalex.org/W2067251611","https://openalex.org/W2079417161","https://openalex.org/W2167340365","https://openalex.org/W2318981786","https://openalex.org/W2322936862","https://openalex.org/W2334782222","https://openalex.org/W2346044757","https://openalex.org/W2774225432","https://openalex.org/W2897449364","https://openalex.org/W2901136733","https://openalex.org/W2903158431","https://openalex.org/W2914335791","https://openalex.org/W3035130434","https://openalex.org/W3038043242","https://openalex.org/W3098085399","https://openalex.org/W3156929195","https://openalex.org/W3172128028","https://openalex.org/W4205131338","https://openalex.org/W4206021986","https://openalex.org/W4213251304","https://openalex.org/W6756486208"],"related_works":["https://openalex.org/W2096013579","https://openalex.org/W52153049","https://openalex.org/W1760611253","https://openalex.org/W1589140671","https://openalex.org/W1515117609","https://openalex.org/W4323315247","https://openalex.org/W2294884454","https://openalex.org/W3169161914","https://openalex.org/W4321379664","https://openalex.org/W2211790881"],"abstract_inverted_index":{"Autonomously":[0],"selecting":[1],"the":[2,20,49,53,63,71,82,91,96,108,111,133,141,150,153,158,167,175],"right":[3],"sequence":[4],"of":[5,22,31,73,80,115,152,174,194],"locations":[6],"to":[7,43,48,61,122,125,131,172],"sample":[8,135],"is":[9,42],"critical":[10],"during":[11],"exploration":[12],"missions":[13],"in":[14,39,85],"unknown":[15,40,92,113],"environments,":[16],"with":[17,52,99],"constraints":[18],"on":[19,185],"number":[21],"samples":[23,57,168],"that":[24,110,129,140,164,169],"can":[25],"be":[26,173],"collected,":[27],"and":[28,95,188],"a":[29,78,86,127,161,181,191,195],"possibility":[30],"system":[32],"failure.":[33],"A":[34],"key":[35],"idea":[36],"for":[37],"decision-making":[38],"environments":[41],"exploit":[44],"side":[45],"information":[46,54],"available":[47],"agent,":[50],"combined":[51],"gained":[55],"from":[56],"collected":[58],"so":[59],"far,":[60],"estimate":[62],"sampling":[64,74,93,100,183],"values.":[65],"In":[66],"this":[67,116],"paper,":[68],"we":[69],"pose":[70],"problem":[72,79,184],"site":[75],"selection":[76],"as":[77],"finding":[81],"optimal":[83],"policy":[84],"Markov":[87,117],"decision":[88,118],"process":[89,119],"modeling":[90],"values":[94],"outcomes":[97],"associated":[98],"attempts":[101,130],"at":[102],"different":[103],"locations.":[104],"Our":[105,178],"solution":[106],"exploits":[107],"fact":[109],"partially":[112],"rewards":[114],"are":[120,170],"correlated":[121],"each":[123],"other":[124],"devise":[126],"strategy":[128,163],"maximize":[132],"total":[134],"value":[136],"while":[137],"also":[138],"ensuring":[139],"agent":[142],"achieves":[143],"its":[144],"minimum":[145],"mission":[146],"requirement.":[147],"We":[148],"validate":[149],"utility":[151],"proposed":[154],"approach":[155],"by":[156],"evaluating":[157],"method":[159],"against":[160],"baseline":[162],"pursues":[165],"collecting":[166],"estimated":[171],"highest":[176],"value.":[177],"evaluations":[179],"use":[180],"simulated":[182],"Martian":[186],"terrain":[187],"using":[189],"OceanWATERS,":[190],"high-fidelity":[192],"simulator":[193],"future":[196],"Europa":[197],"lander":[198],"mission.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}