{"id":"https://openalex.org/W2577017106","doi":"https://doi.org/10.1109/ecc.2016.7810561","title":"Multi-agent motion planning and coordination in polygonal environments using vector fields and model predictive control","display_name":"Multi-agent motion planning and coordination in polygonal environments using vector fields and model predictive control","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2577017106","doi":"https://doi.org/10.1109/ecc.2016.7810561","mag":"2577017106"},"language":"en","primary_location":{"id":"doi:10.1109/ecc.2016.7810561","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecc.2016.7810561","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 European Control Conference (ECC)","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/A5108400288","display_name":"Rashmi Hegde","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rashmi Hegde","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059647993","display_name":"Dimitra Panagou","orcid":"https://orcid.org/0000-0002-4547-167X"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitra Panagou","raw_affiliation_strings":["Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.5032,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.78256619,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1856","last_page":"1861"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":1.0,"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":1.0,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9994999766349792,"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/T10879","display_name":"Robotic Locomotion and Control","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.7405961751937866},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6029233336448669},{"id":"https://openalex.org/keywords/vector-field","display_name":"Vector field","score":0.5860805511474609},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.5799989700317383},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5657169818878174},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.5038239359855652},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.4995236396789551},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.47926971316337585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2831149101257324},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.2745008170604706},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23343166708946228},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.17023825645446777},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.086295485496521}],"concepts":[{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.7405961751937866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6029233336448669},{"id":"https://openalex.org/C91188154","wikidata":"https://www.wikidata.org/wiki/Q186247","display_name":"Vector field","level":2,"score":0.5860805511474609},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.5799989700317383},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5657169818878174},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5038239359855652},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.4995236396789551},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.47926971316337585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2831149101257324},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2745008170604706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23343166708946228},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.17023825645446777},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.086295485496521},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ecc.2016.7810561","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ecc.2016.7810561","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 European Control Conference (ECC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W8369482","https://openalex.org/W101508493","https://openalex.org/W115622331","https://openalex.org/W131069610","https://openalex.org/W1140590240","https://openalex.org/W1424654272","https://openalex.org/W1514191729","https://openalex.org/W1521785144","https://openalex.org/W1563826663","https://openalex.org/W1591465481","https://openalex.org/W1777783943","https://openalex.org/W1969483458","https://openalex.org/W1978701338","https://openalex.org/W2014428146","https://openalex.org/W2019080073","https://openalex.org/W2019586060","https://openalex.org/W2025984802","https://openalex.org/W2044709959","https://openalex.org/W2055201760","https://openalex.org/W2059007332","https://openalex.org/W2069830673","https://openalex.org/W2071257796","https://openalex.org/W2074802943","https://openalex.org/W2103120971","https://openalex.org/W2110144538","https://openalex.org/W2112097268","https://openalex.org/W2116773335","https://openalex.org/W2125409550","https://openalex.org/W2128990851","https://openalex.org/W2151958719","https://openalex.org/W2152427109","https://openalex.org/W2153612202","https://openalex.org/W2164402964","https://openalex.org/W2169528473","https://openalex.org/W2611243847","https://openalex.org/W2987233852","https://openalex.org/W4242811155","https://openalex.org/W4250730679","https://openalex.org/W4298410530","https://openalex.org/W6600356965","https://openalex.org/W6605295560","https://openalex.org/W6668959476"],"related_works":["https://openalex.org/W2930076404","https://openalex.org/W4253519380","https://openalex.org/W2071957557","https://openalex.org/W2596413128","https://openalex.org/W4391249562","https://openalex.org/W2356867392","https://openalex.org/W2782776446","https://openalex.org/W3043170174","https://openalex.org/W2155948905","https://openalex.org/W4380590094"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,60],"extend":[4],"earlier":[5],"work":[6],"on":[7,50],"motion":[8],"planning":[9],"and":[10,111,142],"coordination":[11,132,141],"of":[12,17,45,58,64,102,119,128],"multiple":[13],"agents,":[14],"to":[15,25,93,137],"environments":[16],"arbitrary":[18],"polygonal":[19],"obstacles,":[20],"using":[21],"non-gradient":[22],"vector":[23,39,65,84],"fields":[24,40,66],"steer":[26],"each":[27],"agent":[28],"towards":[29],"their":[30,46],"goal":[31],"configurations":[32],"while":[33],"avoiding":[34],"collisions.":[35],"We":[36,81],"formulate":[37],"the":[38,43,56,71,83,103],"so":[41],"that":[42],"pattern":[44],"integral":[47,68],"curves":[48,69],"depends":[49],"a":[51,62,76,138],"parameter":[52],"\u03bb.":[53],"By":[54],"manipulating":[55],"value":[57],"\u03bb,":[59],"obtain":[61],"set":[63],"whose":[67],"define":[70],"flow":[72],"lines":[73],"for":[74,97,108,130],"an":[75],"priori":[77],"known":[78],"obstacle":[79],"environment.":[80],"use":[82],"field":[85],"design":[86],"in":[87,123],"tandem":[88],"with":[89],"model":[90,120],"predictive":[91,121],"control":[92,122,125,143],"compute":[94],"safe":[95],"trajectories":[96],"multi-agent":[98,131],"systems.":[99],"The":[100,117],"competence":[101],"proposed":[104],"methodology":[105],"is":[106,133],"demonstrated":[107],"both":[109],"static":[110],"dynamic":[112],"environment":[113],"via":[114],"simulation":[115],"results.":[116],"efficacy":[118],"achieving":[124],"trajectories,":[126],"free":[127],"chattering,":[129],"validated":[134],"through":[135],"comparison":[136],"state":[139],"feedback":[140],"protocol.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
