{"id":"https://openalex.org/W4388145440","doi":"https://doi.org/10.1109/tits.2023.3323210","title":"Dynamic Obstacle Avoidance System Based on Rapid Instance Segmentation Network","display_name":"Dynamic Obstacle Avoidance System Based on Rapid Instance Segmentation Network","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4388145440","doi":"https://doi.org/10.1109/tits.2023.3323210"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3323210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3323210","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5114095681","display_name":"Hongmin Mu","orcid":null},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongmin Mu","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102751264","display_name":"Gang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Zhang","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032129553","display_name":"Zhe Ma","orcid":"https://orcid.org/0009-0007-3320-229X"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Ma","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081318069","display_name":"MengChu Zhou","orcid":"https://orcid.org/0000-0002-5408-8752"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengchu Zhou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079155612","display_name":"Zhengcai Cao","orcid":"https://orcid.org/0000-0003-0344-0207"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengcai Cao","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5114095681"],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":2.5847,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.89015083,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"25","issue":"5","first_page":"4578","last_page":"4592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9945999979972839,"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/computer-science","display_name":"Computer science","score":0.7719110250473022},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.7615789771080017},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.7282109260559082},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6115924119949341},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5706367492675781},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.5583291053771973},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5531905889511108},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.517586350440979},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5021576881408691},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4529513120651245},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4459788501262665},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.44276827573776245},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41178521513938904},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.21958711743354797},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19401249289512634},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17641982436180115},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.15640351176261902},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13533315062522888}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7719110250473022},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.7615789771080017},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.7282109260559082},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6115924119949341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5706367492675781},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.5583291053771973},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5531905889511108},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.517586350440979},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5021576881408691},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4529513120651245},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4459788501262665},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.44276827573776245},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41178521513938904},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.21958711743354797},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19401249289512634},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17641982436180115},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.15640351176261902},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13533315062522888},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2023.3323210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3323210","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1309666564","display_name":null,"funder_award_id":"92148202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3418878103","display_name":null,"funder_award_id":"L223019","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G36332496","display_name":null,"funder_award_id":"52175002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2117228865","https://openalex.org/W2123436043","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2207120639","https://openalex.org/W2318964089","https://openalex.org/W2340897893","https://openalex.org/W2531409750","https://openalex.org/W2565639579","https://openalex.org/W2601564443","https://openalex.org/W2750753797","https://openalex.org/W2784327374","https://openalex.org/W2792585818","https://openalex.org/W2798122215","https://openalex.org/W2805440904","https://openalex.org/W2885010430","https://openalex.org/W2928165649","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2993182889","https://openalex.org/W2995958891","https://openalex.org/W2997207016","https://openalex.org/W2998152504","https://openalex.org/W2998738671","https://openalex.org/W2999219213","https://openalex.org/W3012268349","https://openalex.org/W3013630101","https://openalex.org/W3024046433","https://openalex.org/W3026794402","https://openalex.org/W3030434541","https://openalex.org/W3034475678","https://openalex.org/W3041430429","https://openalex.org/W3047032303","https://openalex.org/W3089613853","https://openalex.org/W3098056556","https://openalex.org/W3106250896","https://openalex.org/W3130349375","https://openalex.org/W3134257222","https://openalex.org/W3138516171","https://openalex.org/W3203235787","https://openalex.org/W4225348272","https://openalex.org/W4283030623","https://openalex.org/W4285505472","https://openalex.org/W4312251806","https://openalex.org/W4312460151","https://openalex.org/W4312504688","https://openalex.org/W4319996400","https://openalex.org/W6750469568","https://openalex.org/W6784930956","https://openalex.org/W6798837711"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2913749762","https://openalex.org/W2321940404","https://openalex.org/W2140606111","https://openalex.org/W2981141433","https://openalex.org/W2991662304","https://openalex.org/W2794689129","https://openalex.org/W2975575631","https://openalex.org/W2785353696","https://openalex.org/W2355860162"],"abstract_inverted_index":{"To":[0,59,81,124,154],"assist":[1],"the":[2,83,111,126],"Partially":[3],"Sighted":[4],"and":[5,32,45,56,171,196],"Visually":[6],"Impaired":[7],"(PSVI),":[8],"a":[9,68,94,120,133,159],"variety":[10],"of":[11,30,86,104,114,128],"Obstacle":[12],"Avoidance":[13],"(OA)":[14],"methods":[15,20],"have":[16],"been":[17],"developed.":[18],"These":[19],"mostly":[21],"use":[22],"depth":[23],"cameras":[24],"for":[25,78,89,145],"distance":[26,139],"measurement":[27],"in":[28],"terms":[29],"perception,":[31],"communicate":[33],"to":[34,41,52,54,66,141,176,189],"users":[35,188],"through":[36,191],"voice":[37],"broadcasts.":[38],"However,":[39],"due":[40],"insufficient":[42],"detection":[43],"accuracy":[44,85],"slow":[46],"system":[47,71,184],"response,":[48],"they":[49],"are":[50],"difficult":[51],"apply":[53],"narrow":[55],"multi-pedestrian":[57],"areas.":[58],"overcome":[60],"this":[61,63,130],"difficulty,":[62],"work":[64,131],"aims":[65],"develop":[67],"dynamic":[69],"OA":[70],"using":[72],"an":[73,115],"improved":[74],"instance":[75],"segmentation":[76,84],"network":[77],"high-precision":[79],"detection.":[80],"improve":[82,125],"accessible":[87],"paths":[88,144],"PSVI":[90,146,187],"users,":[91,147],"it":[92,157],"proposes":[93,158],"new":[95],"2D":[96],"convolution":[97],"unit":[98,108],"that":[99,181],"couples":[100],"multi-scale":[101],"receptive":[102],"fields":[103],"deep":[105],"features.":[106],"This":[107],"focuses":[109],"on":[110,164],"global":[112],"context":[113],"input":[116],"image":[117],"by":[118],"constructing":[119],"hierarchical":[121],"residual-like":[122],"structure.":[123],"efficiency":[127],"exploration,":[129],"adopts":[132],"bidirectional":[134],"A*":[135],"algorithm":[136,162],"with":[137],"safety":[138,166],"constraints":[140],"plan":[142],"optimal":[143],"thus":[148],"avoiding":[149],"their":[150],"trial-and-error":[151],"path":[152],"finding.":[153],"ensure":[155],"safety,":[156],"collision":[160],"avoidance":[161],"based":[163],"regional":[165],"analysis,":[167],"which":[168],"can":[169,185],"generate":[170],"transmit":[172],"timely":[173],"vibration":[174],"response":[175],"users.":[177],"Experimental":[178],"results":[179],"demonstrate":[180],"our":[182],"developed":[183],"help":[186],"pass":[190],"those":[192],"challenging":[193],"areas":[194],"safely":[195],"effectively.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":7}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}