{"id":"https://openalex.org/W2790496449","doi":"https://doi.org/10.1109/spac.2017.8304325","title":"Motion planning for unmanned vehicle based on hybrid deep learning","display_name":"Motion planning for unmanned vehicle based on hybrid deep learning","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2790496449","doi":"https://doi.org/10.1109/spac.2017.8304325","mag":"2790496449"},"language":"en","primary_location":{"id":"doi:10.1109/spac.2017.8304325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2017.8304325","pdf_url":null,"source":{"id":"https://openalex.org/S4306498208","display_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","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/A5070747080","display_name":"Chaoxia Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaoxia Shi","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048899046","display_name":"Xiaogen Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaogen Lan","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063433935","display_name":"Yanqing Wang","orcid":"https://orcid.org/0000-0001-9412-5346"},"institutions":[{"id":"https://openalex.org/I4210128418","display_name":"Nanjing Xiaozhuang University","ror":"https://ror.org/03fnv7n42","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128418"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanqing Wang","raw_affiliation_strings":["School of Information Engineering, Nanjing Xiaozhuang University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Nanjing Xiaozhuang University, Nanjing, China","institution_ids":["https://openalex.org/I4210128418"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070747080"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.591,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81043478,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"473","last_page":"478"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9987000226974487,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.6648808121681213},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.5874559879302979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5376967191696167},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.49851393699645996},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4160650074481964},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35978299379348755},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.16278696060180664}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6648808121681213},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5874559879302979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5376967191696167},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.49851393699645996},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4160650074481964},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35978299379348755},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.16278696060180664}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spac.2017.8304325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2017.8304325","pdf_url":null,"source":{"id":"https://openalex.org/S4306498208","display_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W1979641637","https://openalex.org/W2088335308","https://openalex.org/W2154844948","https://openalex.org/W2227909145","https://openalex.org/W2257979135","https://openalex.org/W2298605637","https://openalex.org/W2383388568","https://openalex.org/W2483814582","https://openalex.org/W2907275873","https://openalex.org/W2964167449","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3009238340","https://openalex.org/W3116076068","https://openalex.org/W2229312674"],"abstract_inverted_index":{"Motion":[0],"planning,":[1],"as":[2,122,124],"a":[3,40,52,91,119,148],"principle":[4],"technology":[5],"for":[6,157],"autonomous":[7],"navigation":[8,142],"of":[9,18,25,31,46,82,155],"unmanned":[10,158],"vehicle,":[11],"is":[12,36,61],"mostly":[13],"realized":[14],"by":[15,86],"the":[16,23,26,29,32,50,80,83,133],"mode":[17],"pre-programming.":[19],"However,":[20],"due":[21],"to":[22,38,71,117],"complexity":[24],"environment":[27,145],"and":[28,77,146],"uncertainty":[30],"sensor":[33],"information,":[34],"it":[35],"difficult":[37],"design":[39],"general":[41],"motion":[42,53,135,152],"planning":[43,54,136,153],"system":[44,55,64,137],"capable":[45,154],"self-learning.":[47],"To":[48],"solve":[49],"problem,":[51],"based":[56,95],"on":[57,96,151],"hybrid":[58],"deep":[59],"learning":[60],"addressed.":[62],"The":[63,128],"first":[65],"uses":[66],"convolutional":[67],"neural":[68,98,112],"networks":[69,99,113],"(CNN)":[70],"construct":[72,118],"an":[73,125],"auto":[74],"encoder":[75],"model":[76,94,121],"thus":[78],"reduce":[79],"dimension":[81],"input":[84],"image":[85],"encoding.":[87],"It":[88],"then":[89],"constructs":[90],"path":[92],"tracking":[93],"recurrent":[97],"(RNN)":[100],"which":[101],"has":[102],"advantage":[103],"in":[104,143],"dealing":[105],"with":[106],"sequential":[107],"data.":[108],"Finally,":[109],"full":[110],"connected":[111],"(FCNN)":[114],"are":[115],"used":[116],"control":[120],"well":[123],"evaluation":[126],"model.":[127],"experimental":[129],"results":[130],"demonstrate":[131],"that":[132],"proposed":[134],"can":[138],"realize":[139],"robust":[140],"visual":[141],"road":[144],"supply":[147],"promising":[149],"scheme":[150],"self-learning":[156],"vehicle.":[159]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
