{"id":"https://openalex.org/W4405785268","doi":"https://doi.org/10.1109/iros58592.2024.10802371","title":"Social Navigation in Crowded Environments with Model Predictive Control and Deep Learning-Based Human Trajectory Prediction","display_name":"Social Navigation in Crowded Environments with Model Predictive Control and Deep Learning-Based Human Trajectory Prediction","publication_year":2024,"publication_date":"2024-10-14","ids":{"openalex":"https://openalex.org/W4405785268","doi":"https://doi.org/10.1109/iros58592.2024.10802371"},"language":"en","primary_location":{"id":"doi:10.1109/iros58592.2024.10802371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5065617320","display_name":"Viet-Anh Le","orcid":"https://orcid.org/0000-0002-9829-7150"},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Viet-Anh Le","raw_affiliation_strings":["University of Delaware,Department of Mechanical Engineering,DE,USA,19716"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Delaware,Department of Mechanical Engineering,DE,USA,19716","institution_ids":["https://openalex.org/I86501945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068009319","display_name":"Behdad Chalaki","orcid":"https://orcid.org/0000-0002-3055-1693"},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Behdad Chalaki","raw_affiliation_strings":["Honda Research Institute USA, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA, Inc","institution_ids":["https://openalex.org/I4210145184"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024302009","display_name":"Vaishnav Tadiparthi","orcid":"https://orcid.org/0000-0001-9897-0600"},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vaishnav Tadiparthi","raw_affiliation_strings":["Honda Research Institute USA, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA, Inc","institution_ids":["https://openalex.org/I4210145184"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001543635","display_name":"Hossein Nourkhiz Mahjoub","orcid":"https://orcid.org/0000-0002-8380-3241"},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hossein Nourkhiz Mahjoub","raw_affiliation_strings":["Honda Research Institute USA, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA, Inc","institution_ids":["https://openalex.org/I4210145184"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033048366","display_name":"Jovin D\u2019sa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jovin D\u2019Sa","raw_affiliation_strings":["Honda Research Institute USA, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA, Inc","institution_ids":["https://openalex.org/I4210145184"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032101438","display_name":"Ehsan Moradi\u2010Pari","orcid":"https://orcid.org/0000-0002-4822-3196"},"institutions":[{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ehsan Moradi-Pari","raw_affiliation_strings":["Honda Research Institute USA, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA, Inc","institution_ids":["https://openalex.org/I4210145184"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4793","last_page":"4799"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10370","display_name":"Traffic and Road Safety","score":0.9616000056266785,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9610999822616577,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/trajectory","display_name":"Trajectory","score":0.8270341157913208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6504043936729431},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5384879112243652},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.45719045400619507},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4469958543777466},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.438385546207428},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3363536596298218},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3358505666255951}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8270341157913208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6504043936729431},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5384879112243652},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.45719045400619507},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4469958543777466},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.438385546207428},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3363536596298218},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3358505666255951},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros58592.2024.10802371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2059993653","https://openalex.org/W2123871098","https://openalex.org/W2140542425","https://openalex.org/W2142943472","https://openalex.org/W2167052694","https://openalex.org/W2424778531","https://openalex.org/W2492629073","https://openalex.org/W2604216058","https://openalex.org/W2604372349","https://openalex.org/W2842089854","https://openalex.org/W2890001928","https://openalex.org/W2892105102","https://openalex.org/W2894928537","https://openalex.org/W2963001155","https://openalex.org/W2963114745","https://openalex.org/W2964319688","https://openalex.org/W3115517346","https://openalex.org/W3124260346","https://openalex.org/W3134972302","https://openalex.org/W3142049818","https://openalex.org/W3155186850","https://openalex.org/W4221154737","https://openalex.org/W4226016029","https://openalex.org/W4315488806","https://openalex.org/W4383109004","https://openalex.org/W4383109360","https://openalex.org/W4383112515","https://openalex.org/W4387088911","https://openalex.org/W4389665364","https://openalex.org/W6853961047"],"related_works":["https://openalex.org/W1990079087","https://openalex.org/W3202234113","https://openalex.org/W2101188133","https://openalex.org/W4248731570","https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W2381210024","https://openalex.org/W3131574667","https://openalex.org/W4380075502","https://openalex.org/W2556120871"],"abstract_inverted_index":{"Navigating":[0],"a":[1,4,57],"robot":[2,47,105],"among":[3,108],"crowd":[5],"has":[6],"received":[7],"increasing":[8],"attention":[9],"from":[10],"researchers":[11],"over":[12],"the":[13,19,27,45,70,75,86,94,104,112],"last":[14],"few":[15],"decades,":[16],"resulting":[17],"in":[18,118],"emergence":[20],"of":[21,29,72,77,80,114,121],"numerous":[22],"approaches":[23],"aimed":[24],"at":[25,82],"addressing":[26],"problem":[28,48],"social":[30,53,63,123],"navigation":[31,124],"to":[32,43,106],"date.":[33],"Our":[34],"proposed":[35,116],"approach":[36,117],"couples":[37],"agent":[38],"motion":[39],"prediction":[40,60,76],"and":[41,125],"planning":[42],"avoid":[44],"freezing":[46],"while":[49],"simultaneously":[50],"capturing":[51],"multi-agent":[52],"interactions":[54],"by":[55],"utilizing":[56],"state-of-the-art":[58,130],"trajectory":[59],"model":[61,67],"i.e.,":[62],"long":[64],"short-term":[65],"memory":[66],"(Social-LSTM).":[68],"Leveraging":[69],"output":[71],"Social-LSTM":[73],"for":[74,103],"future":[78,89],"trajectories":[79],"pedestrians":[81],"each":[83],"time-step":[84],"given":[85],"robot\u2019s":[87],"possible":[88],"actions,":[90],"our":[91,115],"framework":[92],"computes":[93],"optimal":[95],"control":[96],"action":[97],"using":[98],"Model":[99],"Predictive":[100],"Control":[101],"(MPC)":[102],"navigate":[107],"pedestrians.":[109],"We":[110],"demonstrate":[111],"effectiveness":[113],"multiple":[119],"scenarios":[120],"simulated":[122],"compare":[126],"it":[127],"against":[128],"several":[129],"reinforcement":[131],"learning-based":[132],"methods.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":8}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}