{"id":"https://openalex.org/W2930955510","doi":"https://doi.org/10.1109/hri.2019.8673017","title":"Stop Doing it! Approaching Strategy for a Robot to Admonish Pedestrians","display_name":"Stop Doing it! Approaching Strategy for a Robot to Admonish Pedestrians","publication_year":2019,"publication_date":"2019-03-01","ids":{"openalex":"https://openalex.org/W2930955510","doi":"https://doi.org/10.1109/hri.2019.8673017","mag":"2930955510"},"language":"en","primary_location":{"id":"doi:10.1109/hri.2019.8673017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hri.2019.8673017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)","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/A5036899430","display_name":"Kazuki Mizumaru","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kazuki Mizumaru","raw_affiliation_strings":["Hokkaido University, Hokkaido, Japan"],"affiliations":[{"raw_affiliation_string":"Hokkaido University, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000494459","display_name":"Satoru Satake","orcid":"https://orcid.org/0000-0001-6482-1877"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Satoru Satake","raw_affiliation_strings":["ATR Inteligent Robotics and Communication Laboratories, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"ATR Inteligent Robotics and Communication Laboratories, Kyoto, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028939608","display_name":"Takayuki Kanda","orcid":"https://orcid.org/0000-0002-9546-5825"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayuki Kanda","raw_affiliation_strings":["Kyoto University, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049920990","display_name":"Tetsuo Ono","orcid":"https://orcid.org/0000-0001-7881-7318"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuo Ono","raw_affiliation_strings":["Hokkaido University, Hokkaido, Japan"],"affiliations":[{"raw_affiliation_string":"Hokkaido University, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036899430"],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":null,"apc_paid":null,"fwci":4.493,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.94251858,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"449","last_page":"457"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9991000294685364,"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":0.9991000294685364,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9605000019073486,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.78580641746521},{"id":"https://openalex.org/keywords/guard","display_name":"Guard (computer science)","score":0.7332091927528381},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.573251485824585},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5727612972259521},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4772743582725525},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.4489622712135315},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.345123827457428},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0942777693271637}],"concepts":[{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.78580641746521},{"id":"https://openalex.org/C141141315","wikidata":"https://www.wikidata.org/wiki/Q2379942","display_name":"Guard (computer science)","level":2,"score":0.7332091927528381},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.573251485824585},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5727612972259521},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4772743582725525},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.4489622712135315},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.345123827457428},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0942777693271637},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hri.2019.8673017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hri.2019.8673017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)","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":29,"referenced_works":["https://openalex.org/W964305833","https://openalex.org/W1549076334","https://openalex.org/W1608844340","https://openalex.org/W1911390924","https://openalex.org/W1978124457","https://openalex.org/W1978680804","https://openalex.org/W1987768879","https://openalex.org/W1989205184","https://openalex.org/W1997843800","https://openalex.org/W2007223396","https://openalex.org/W2024986232","https://openalex.org/W2046213647","https://openalex.org/W2050850176","https://openalex.org/W2070707168","https://openalex.org/W2077638917","https://openalex.org/W2099840956","https://openalex.org/W2110750157","https://openalex.org/W2128873520","https://openalex.org/W2129491278","https://openalex.org/W2147297121","https://openalex.org/W2150715964","https://openalex.org/W2159408972","https://openalex.org/W2160379528","https://openalex.org/W2161082723","https://openalex.org/W2162528857","https://openalex.org/W2164304727","https://openalex.org/W2166138517","https://openalex.org/W2294197530","https://openalex.org/W4243724405"],"related_works":["https://openalex.org/W4254637722","https://openalex.org/W2980401999","https://openalex.org/W2903025760","https://openalex.org/W4289147272","https://openalex.org/W2122871747","https://openalex.org/W3114279067","https://openalex.org/W2581059419","https://openalex.org/W2401800146","https://openalex.org/W1603042966","https://openalex.org/W2612216462"],"abstract_inverted_index":{"We":[0,9,15,38,95],"modeled":[1],"a":[2,17,22,35,90,104,109,129,144,152],"robot's":[3],"approaching":[4,51,56],"behavior":[5],"for":[6,30,34],"giving":[7],"admonishment.":[8],"started":[10],"by":[11],"analyzing":[12],"human":[13],"behaviors.":[14],"conducted":[16,108],"data":[18],"collection":[19],"in":[20,26,53,92],"which":[21],"guard":[23],"approached":[24],"others":[25],"two":[27,55,63],"ways:":[28],"1)":[29],"admonishment,":[31],"and":[32,46],"2)":[33],"friendly":[36,48,77,156],"purpose.":[37],"analyzed":[39],"the":[40,43,47,54,67,76,83,86,93,100,114,117,147,155],"difference":[41],"between":[42],"admonishing":[44,68,101],"approach":[45,69,78,102,157],"approach.":[49],"The":[50,133],"trajectories":[52],"types":[57],"are":[58,62],"similar;":[59],"nevertheless,":[60],"there":[61,88],"subtle":[64],"differences.":[65],"First,":[66],"is":[70,89,121],"slightly":[71],"faster":[72],"(1.3":[73],"m/sec)":[74],"than":[75,150],"(1.1":[79],"m/sec).":[80],"Second,":[81],"at":[82],"end":[84],"of":[85,99,116],"approach,":[87],"`shortcut'":[91],"trajectory.":[94],"implemented":[96],"this":[97],"model":[98],"into":[103],"robot.":[105],"Finally,":[106],"we":[107],"field":[110],"experiment":[111],"to":[112,123,141],"verify":[113],"effectiveness":[115],"model.":[118],"A":[119],"robot":[120,145,153],"used":[122],"admonish":[124],"people":[125,139],"who":[126],"were":[127],"using":[128,146,154],"smartphone":[130],"while":[131],"walking.":[132],"result":[134],"shows":[135],"that":[136],"significantly":[137],"more":[138],"yield":[140],"admonishment":[142],"from":[143,151],"proposed":[148],"method":[149],"method.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}