{"id":"https://openalex.org/W4308567452","doi":"https://doi.org/10.23919/wac55640.2022.9934448","title":"Object Detection-Based Reinforcement Learning for Autonomous Point-to-Point Navigation","display_name":"Object Detection-Based Reinforcement Learning for Autonomous Point-to-Point Navigation","publication_year":2022,"publication_date":"2022-10-11","ids":{"openalex":"https://openalex.org/W4308567452","doi":"https://doi.org/10.23919/wac55640.2022.9934448"},"language":"en","primary_location":{"id":"doi:10.23919/wac55640.2022.9934448","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wac55640.2022.9934448","pdf_url":null,"source":{"id":"https://openalex.org/S4363606418","display_name":"2022 World Automation Congress (WAC)","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":"2022 World Automation Congress (WAC)","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/A5064519932","display_name":"Tyrell Lewis","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tyrell Lewis","raw_affiliation_strings":["The University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,TX,78249"],"affiliations":[{"raw_affiliation_string":"The University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,TX,78249","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016189206","display_name":"Alexander Ibarra","orcid":"https://orcid.org/0000-0001-5916-776X"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Ibarra","raw_affiliation_strings":["The University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,TX,78249"],"affiliations":[{"raw_affiliation_string":"The University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,TX,78249","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113537394","display_name":"Mo Jamshidi","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mo Jamshidi","raw_affiliation_strings":["The University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,TX,78249"],"affiliations":[{"raw_affiliation_string":"The University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,TX,78249","institution_ids":["https://openalex.org/I45438204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5064519932"],"corresponding_institution_ids":["https://openalex.org/I45438204"],"apc_list":null,"apc_paid":null,"fwci":0.0602,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.29074576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"394","last_page":"399"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9997000098228455,"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":0.9997000098228455,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9983999729156494,"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":0.7065173983573914},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6819382309913635},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6422863602638245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6348583698272705},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6328436136245728},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5762709379196167},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5253579020500183},{"id":"https://openalex.org/keywords/point-target","display_name":"Point target","score":0.41762423515319824},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.1447390615940094},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07668736577033997},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.05711016058921814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7065173983573914},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6819382309913635},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6422863602638245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6348583698272705},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6328436136245728},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5762709379196167},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5253579020500183},{"id":"https://openalex.org/C2778999744","wikidata":"https://www.wikidata.org/wiki/Q7208292","display_name":"Point target","level":3,"score":0.41762423515319824},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.1447390615940094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07668736577033997},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.05711016058921814},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/wac55640.2022.9934448","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wac55640.2022.9934448","pdf_url":null,"source":{"id":"https://openalex.org/S4363606418","display_name":"2022 World Automation Congress (WAC)","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":"2022 World Automation Congress (WAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2146881125","https://openalex.org/W2164769497","https://openalex.org/W2342662072","https://openalex.org/W2605102758","https://openalex.org/W2736601468","https://openalex.org/W2761873684","https://openalex.org/W2782298334","https://openalex.org/W2796290181","https://openalex.org/W2885164411","https://openalex.org/W2886498421","https://openalex.org/W2889987506","https://openalex.org/W2890991980","https://openalex.org/W2900055155","https://openalex.org/W3009928773","https://openalex.org/W3011144238","https://openalex.org/W3104515094","https://openalex.org/W3106250896","https://openalex.org/W3113254760","https://openalex.org/W3207502053","https://openalex.org/W3216772467","https://openalex.org/W4207016512","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6639102338","https://openalex.org/W6704571135","https://openalex.org/W6741002519","https://openalex.org/W6750227808","https://openalex.org/W6753526802","https://openalex.org/W6774815639","https://openalex.org/W6785652829","https://openalex.org/W6804601995","https://openalex.org/W6922278269"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W2031695474","https://openalex.org/W4292830139","https://openalex.org/W4319309705","https://openalex.org/W1828306593","https://openalex.org/W2350038061","https://openalex.org/W2393963654"],"abstract_inverted_index":{"Autonomous":[0],"navigation":[1,113,153],"has":[2],"been":[3],"a":[4,63,105,117,136],"fundamental":[5],"area":[6],"of":[7,29,33,98],"research":[8],"for":[9,103,133],"real-world":[10],"mobile":[11,107],"robotic":[12],"applications,":[13],"having":[14],"widespread":[15],"utility":[16],"across":[17,79],"many":[18],"industries":[19],"from":[20,53],"warehouse":[21],"package":[22],"delivery":[23],"to":[24,60,109,141,148,156],"residential":[25],"cleaning":[26],"services.":[27],"Because":[28],"the":[30,34,54,58,74,96,99,151],"complex":[31,66],"nature":[32],"robot\u2019s":[35],"environment,":[36],"several":[37],"challenges":[38],"have":[39],"prevented":[40],"effectively":[41],"implementing":[42],"reinforcement":[43],"learning-based":[44],"algorithms":[45],"trained":[46],"in":[47,76,114,120,162],"simulation.":[48],"While":[49],"difficulties":[50],"can":[51],"arise":[52],"virtual":[55],"environment":[56],"lacking":[57],"sophistication":[59],"represent":[61],"such":[62],"large":[64],"and":[65,87],"state":[67],"space":[68],"based":[69],"on":[70],"data-heavy":[71],"sensor":[72],"observations,":[73],"variance":[75],"MDP":[77],"representations":[78],"related":[80,164],"studies":[81],"biases":[82],"their":[83],"fair":[84],"comparison,":[85],"performance,":[86],"repeatability.":[88],"In":[89],"this":[90],"study,":[91],"it":[92],"is":[93,126,130],"found":[94,147],"that":[95],"design":[97],"reward":[100,129,158],"function":[101,159],"used":[102],"training":[104],"vision-based":[106],"agent":[108],"perform":[110],"collision-free":[111],"point-goal":[112,152],"simulation":[115],"plays":[116],"significant":[118],"role":[119],"overall":[121],"performance.":[122],"A":[123],"novel":[124],"approach":[125],"introduced":[127],"where":[128],"also":[131],"granted":[132],"successfully":[134],"detecting":[135],"target":[137],"object":[138],"scaled":[139],"according":[140],"prediction":[142],"confidence.":[143],"This":[144],"strategy":[145],"was":[146],"significantly":[149],"improve":[150],"behavior":[154],"compared":[155],"simpler":[157],"designs":[160],"seen":[161],"similar":[163],"studies.":[165]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
