{"id":"https://openalex.org/W3197674289","doi":"https://doi.org/10.1109/rcar52367.2021.9517362","title":"Socially-Aware Multi-Agent Following with 2D Laser Scans via Deep Reinforcement Learning and Potential Field","display_name":"Socially-Aware Multi-Agent Following with 2D Laser Scans via Deep Reinforcement Learning and Potential Field","publication_year":2021,"publication_date":"2021-07-15","ids":{"openalex":"https://openalex.org/W3197674289","doi":"https://doi.org/10.1109/rcar52367.2021.9517362","mag":"3197674289"},"language":"en","primary_location":{"id":"doi:10.1109/rcar52367.2021.9517362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar52367.2021.9517362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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/A5027262916","display_name":"Yuxiang Cui","orcid":"https://orcid.org/0000-0001-8976-8865"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yuxiang Cui","raw_affiliation_strings":["State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022782194","display_name":"Xiaolong Huang","orcid":"https://orcid.org/0000-0001-6253-433X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaolong Huang","raw_affiliation_strings":["State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371992","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0002-0981-935X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019081110","display_name":"Rong Xiong","orcid":"https://orcid.org/0000-0001-9318-9014"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rong Xiong","raw_affiliation_strings":["State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, P.R. China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5027262916"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3396,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.59348279,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"515","last_page":"520"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9998999834060669,"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":0.9998999834060669,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9988999962806702,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9980999827384949,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.9053371548652649},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.8221085071563721},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.71381676197052},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.7039021849632263},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.6480316519737244},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.611152172088623},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6093791127204895},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5801032781600952},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.46177729964256287},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45431020855903625},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.4175015389919281},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.35019218921661377},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3471968173980713},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.3123030662536621},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12632235884666443},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.07704749703407288},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06973007321357727}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.9053371548652649},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.8221085071563721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71381676197052},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.7039021849632263},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.6480316519737244},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.611152172088623},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6093791127204895},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5801032781600952},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.46177729964256287},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45431020855903625},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.4175015389919281},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.35019218921661377},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3471968173980713},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.3123030662536621},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12632235884666443},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.07704749703407288},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06973007321357727},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/rcar52367.2021.9517362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar52367.2021.9517362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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":27,"referenced_works":["https://openalex.org/W1578421573","https://openalex.org/W1969483458","https://openalex.org/W2008185123","https://openalex.org/W2038498300","https://openalex.org/W2105686579","https://openalex.org/W2209009377","https://openalex.org/W2560345704","https://openalex.org/W2742229085","https://openalex.org/W2787176632","https://openalex.org/W2787938642","https://openalex.org/W2887927966","https://openalex.org/W2891197787","https://openalex.org/W2905187039","https://openalex.org/W2946615175","https://openalex.org/W2959221924","https://openalex.org/W2962769831","https://openalex.org/W2963923407","https://openalex.org/W3003364424","https://openalex.org/W3104395407","https://openalex.org/W3132829070","https://openalex.org/W3206650971","https://openalex.org/W3212470397","https://openalex.org/W4229668751","https://openalex.org/W6730911089","https://openalex.org/W6748839928","https://openalex.org/W6753624969","https://openalex.org/W6785613427"],"related_works":["https://openalex.org/W2794103424","https://openalex.org/W2023024008","https://openalex.org/W1911254468","https://openalex.org/W1506523185","https://openalex.org/W1819938260","https://openalex.org/W2340892746","https://openalex.org/W3005999311","https://openalex.org/W2281433634","https://openalex.org/W2165574943","https://openalex.org/W3009037905"],"abstract_inverted_index":{"Target":[0],"following":[1,62,156],"in":[2,25,51,78,104,126,161,180,190],"dynamic":[3,122,182],"pedestrian":[4],"environments":[5],"is":[6,15,64,141],"an":[7,42],"important":[8],"task":[9],"for":[10,41,138],"mobile":[11],"robots.":[12,157,172],"However,":[13],"it":[14],"challenging":[16],"to":[17,47,89],"keep":[18],"tracking":[19],"the":[20,49,68,80,90,94,99,108,113,132,155,188],"target":[21,50,189],"while":[22,87],"avoiding":[23],"collisions":[24,116],"crowded":[26],"environments,":[27],"especially":[28],"with":[29,98,117,195],"only":[30,56,196],"one":[31],"robot.":[32],"In":[33],"this":[34],"paper,":[35],"we":[36],"propose":[37],"a":[38,52,144,191],"multi-agent":[39,61],"method":[40,177],"arbitrary":[43],"number":[44],"of":[45,71,101,171],"robots":[46,114,185],"follow":[48,187],"socially-aware":[53],"manner":[54,194],"using":[55,149],"2D":[57,197],"laser":[58,102,198],"scans.":[59,199],"The":[60,184],"problem":[63],"tackled":[65],"by":[66,93],"utilizing":[67],"complementary":[69],"strengths":[70],"both":[72,118],"reinforcement":[73,81],"learning":[74,82],"and":[75,121,135,168],"potential":[76,95,146],"field,":[77],"which":[79],"part":[83],"handles":[84],"local":[85],"interactions":[86],"navigating":[88],"goals":[91],"assigned":[92],"field.":[96],"Specifically,":[97],"help":[100,112],"scans":[103],"obstacle":[105,166],"map":[106],"representation,":[107],"learning-based":[109],"policy":[110],"can":[111,186],"avoid":[115],"static":[119],"obstacles":[120,123],"like":[124],"pedestrians":[125],"advance,":[127],"namely":[128],"socially":[129,192],"aware.":[130],"While":[131],"formation":[133],"control":[134],"goal":[136],"assignment":[137],"each":[139],"robot":[140],"obtained":[142],"from":[143,153],"target-centered":[145],"field":[147],"constructed":[148],"aggregated":[150],"state":[151],"information":[152],"all":[154],"Experiments":[158],"are":[159],"conducted":[160],"multiple":[162],"settings,":[163],"including":[164],"random":[165],"distributions":[167],"different":[169],"numbers":[170],"Results":[173],"show":[174],"that":[175],"our":[176],"works":[178],"successfully":[179],"unseen":[181],"environments.":[183],"compliant":[193]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}