{"id":"https://openalex.org/W4401415911","doi":"https://doi.org/10.1109/icra57147.2024.10611689","title":"Gathering Data from Risky Situations with Pareto-Optimal Trajectories","display_name":"Gathering Data from Risky Situations with Pareto-Optimal Trajectories","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401415911","doi":"https://doi.org/10.1109/icra57147.2024.10611689"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10611689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5092397646","display_name":"Brennan Brodt","orcid":null},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brennan Brodt","raw_affiliation_strings":["Boston University,Department of Mechanical Engineering,Boston,MA,USA,02215"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University,Department of Mechanical Engineering,Boston,MA,USA,02215","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035836760","display_name":"Alyssa Pierson","orcid":"https://orcid.org/0000-0002-4885-9119"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alyssa Pierson","raw_affiliation_strings":["Boston University,Department of Mechanical Engineering,Boston,MA,USA,02215"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Boston University,Department of Mechanical Engineering,Boston,MA,USA,02215","institution_ids":["https://openalex.org/I111088046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111088046"],"apc_list":null,"apc_paid":null,"fwci":0.2629,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52051342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"8757","last_page":"8763"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998999834060669,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998999834060669,"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/T12288","display_name":"Optimization and Search Problems","score":0.9955999851226807,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.6719727516174316},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6360398530960083},{"id":"https://openalex.org/keywords/pareto-optimal","display_name":"Pareto optimal","score":0.5737175941467285},{"id":"https://openalex.org/keywords/pareto-analysis","display_name":"Pareto analysis","score":0.4644845128059387},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36289316415786743},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.2916357219219208},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14585551619529724},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10168856382369995}],"concepts":[{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.6719727516174316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6360398530960083},{"id":"https://openalex.org/C2986314615","wikidata":"https://www.wikidata.org/wiki/Q36829","display_name":"Pareto optimal","level":3,"score":0.5737175941467285},{"id":"https://openalex.org/C118127601","wikidata":"https://www.wikidata.org/wiki/Q3797610","display_name":"Pareto analysis","level":3,"score":0.4644845128059387},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36289316415786743},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.2916357219219208},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14585551619529724},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10168856382369995}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10611689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1567710201","https://openalex.org/W1728600603","https://openalex.org/W1977801775","https://openalex.org/W1988737313","https://openalex.org/W2000359213","https://openalex.org/W2000906536","https://openalex.org/W2017335377","https://openalex.org/W2047083748","https://openalex.org/W2088195248","https://openalex.org/W2111664716","https://openalex.org/W2126105956","https://openalex.org/W2133787071","https://openalex.org/W2143897835","https://openalex.org/W2153275400","https://openalex.org/W2483141174","https://openalex.org/W2520459424","https://openalex.org/W2744683172","https://openalex.org/W2771950763","https://openalex.org/W2886553084","https://openalex.org/W2891228419","https://openalex.org/W2957417922","https://openalex.org/W3014541289","https://openalex.org/W3018925423","https://openalex.org/W3023540311","https://openalex.org/W3093571944","https://openalex.org/W3097576879","https://openalex.org/W3130574591","https://openalex.org/W3132537753","https://openalex.org/W3133460950","https://openalex.org/W3135152360","https://openalex.org/W3185545060","https://openalex.org/W3191485867","https://openalex.org/W4200284011","https://openalex.org/W4214933946","https://openalex.org/W4283070192","https://openalex.org/W4285445881","https://openalex.org/W4288709744","https://openalex.org/W4381416043","https://openalex.org/W4383108502","https://openalex.org/W4385248927"],"related_works":["https://openalex.org/W2728870795","https://openalex.org/W1963790170","https://openalex.org/W317165722","https://openalex.org/W2358268639","https://openalex.org/W4300308878","https://openalex.org/W2470758391","https://openalex.org/W2051213170","https://openalex.org/W2166566913","https://openalex.org/W2104917065","https://openalex.org/W1966444509"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,33,42,54,66],"formulation":[4],"for":[5,35,46],"the":[6,26,81],"risk-aware":[7],"path":[8],"planning":[9],"problem":[10],"which":[11],"utilizes":[12],"multi-objective":[13],"optimization":[14],"to":[15,49,94],"dynamically":[16],"plan":[17],"trajectories":[18],"that":[19,44],"satisfy":[20],"multiple":[21],"complex":[22],"mission":[23],"specifications.":[24],"In":[25],"setting":[27],"of":[28,62,83],"persistent":[29],"monitoring,":[30],"we":[31],"develop":[32],"method":[34,73],"representing":[36],"environmental":[37],"information":[38,89],"and":[39,70],"risk":[40],"in":[41],"way":[43],"allows":[45],"local":[47],"sampling":[48,68],"generate":[50],"Pareto-dominant":[51],"solutions":[52],"over":[53],"receding":[55],"horizon.":[56],"We":[57],"propose":[58],"two":[59],"algorithms":[60],"capable":[61],"solving":[63],"these":[64],"problems:":[65],"dense":[67],"approach":[69],"an":[71],"improved":[72],"utilizing":[74],"noisy":[75],"gradient":[76],"descent.":[77],"Simulation":[78],"results":[79],"demonstrate":[80],"efficacy":[82],"our":[84],"methods":[85],"at":[86],"persistently":[87],"gathering":[88],"while":[90],"avoiding":[91],"risk,":[92],"robust":[93],"randomly-generated":[95],"environments.":[96]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}