{"id":"https://openalex.org/W3010830518","doi":"https://doi.org/10.1109/sips47522.2019.9020508","title":"Autonomous UAV with Learned Trajectory Generation and Control","display_name":"Autonomous UAV with Learned Trajectory Generation and Control","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W3010830518","doi":"https://doi.org/10.1109/sips47522.2019.9020508","mag":"3010830518"},"language":"en","primary_location":{"id":"doi:10.1109/sips47522.2019.9020508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sips47522.2019.9020508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Workshop on Signal Processing Systems (SiPS)","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/A5102936390","display_name":"Yilan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yilan Li","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443445","display_name":"Mingyang Li","orcid":"https://orcid.org/0000-0003-4410-0292"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingyang Li","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079524565","display_name":"Amit K. Sanyal","orcid":"https://orcid.org/0000-0002-3258-7841"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Sanyal","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651384","display_name":"Yanzhi Wang","orcid":"https://orcid.org/0000-0002-3024-7990"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanzhi Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018468480","display_name":"Qinru Qiu","orcid":"https://orcid.org/0000-0003-2546-0655"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qinru Qiu","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102936390"],"corresponding_institution_ids":["https://openalex.org/I70983195"],"apc_list":null,"apc_paid":null,"fwci":0.2894,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69029104,"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":"115","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9984999895095825,"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":0.9865999817848206,"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":0.8086169958114624},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.776603102684021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6350109577178955},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.5876078009605408},{"id":"https://openalex.org/keywords/trajectory-optimization","display_name":"Trajectory optimization","score":0.48984333872795105},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4895952343940735},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.4560421109199524},{"id":"https://openalex.org/keywords/attitude-control","display_name":"Attitude control","score":0.4427456855773926},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.41951465606689453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41888633370399475},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4178975224494934},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4159581661224365},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.41468149423599243},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3729765713214874},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2753005623817444},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.20853006839752197},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.19968953728675842},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09975972771644592}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8086169958114624},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.776603102684021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6350109577178955},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.5876078009605408},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.48984333872795105},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4895952343940735},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.4560421109199524},{"id":"https://openalex.org/C155710575","wikidata":"https://www.wikidata.org/wiki/Q83001","display_name":"Attitude control","level":2,"score":0.4427456855773926},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.41951465606689453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41888633370399475},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4178975224494934},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4159581661224365},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.41468149423599243},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3729765713214874},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2753005623817444},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.20853006839752197},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.19968953728675842},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09975972771644592},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","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},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sips47522.2019.9020508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sips47522.2019.9020508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Workshop on Signal Processing Systems (SiPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1512383952","https://openalex.org/W1924639614","https://openalex.org/W2107726111","https://openalex.org/W2173248099","https://openalex.org/W2215378786","https://openalex.org/W2553218715","https://openalex.org/W2596849722","https://openalex.org/W2604459962","https://openalex.org/W2775268899","https://openalex.org/W2890755534","https://openalex.org/W2962887844","https://openalex.org/W2963864421","https://openalex.org/W2964006217","https://openalex.org/W2968430912","https://openalex.org/W4394672593","https://openalex.org/W6639949747","https://openalex.org/W6684921986","https://openalex.org/W6735126893"],"related_works":["https://openalex.org/W2930076404","https://openalex.org/W4253519380","https://openalex.org/W2071957557","https://openalex.org/W2596413128","https://openalex.org/W4391249562","https://openalex.org/W2356867392","https://openalex.org/W2782776446","https://openalex.org/W3043170174","https://openalex.org/W2155948905","https://openalex.org/W2357323510"],"abstract_inverted_index":{"Unmanned":[0],"aerial":[1],"vehicle":[2],"(UAV)":[3],"technology":[4],"is":[5,79,90],"a":[6,40,62,127],"rapidly":[7],"growing":[8],"field":[9],"with":[10],"tremendous":[11],"opportunities":[12],"for":[13,21,92,100],"research":[14],"and":[15,37,49,75,109,130,135,163,187],"applications.":[16],"To":[17],"achieve":[18,182],"true":[19],"autonomy":[20,125],"UAVs":[22],"in":[23,126,133],"the":[24,54,68,137,154,169,173,179],"absence":[25],"of":[26,121,124],"remote":[27],"control,":[28,77],"external":[29],"navigation":[30,34],"aids":[31],"like":[32],"global":[33],"satellite":[35],"systems":[36],"radar":[38],"systems,":[39],"minimum":[41],"energy":[42],"trajectory":[43,74,138,156],"planning":[44],"that":[45,149],"considers":[46],"obstacle":[47],"avoidance":[48],"stability":[50],"control":[51,161,174],"will":[52,157,181],"be":[53,59,83,113],"key.":[55],"Although":[56],"this":[57],"can":[58],"formulated":[60],"as":[61],"constrained":[63],"optimization":[64,99],"problem,":[65],"due":[66],"to":[67,82,95,151,167],"complicated":[69],"non-linear":[70],"relationships":[71],"between":[72],"UAV":[73,128,180],"thrust":[76,162],"it":[78],"almost":[80],"impossible":[81],"solved":[84],"analytically.":[85],"While":[86],"deep":[87,141],"reinforcement":[88,142],"learning":[89,143,176],"known":[91],"its":[93,105],"ability":[94],"provide":[96],"model":[97],"free":[98],"complex":[101],"system":[102,190],"through":[103],"learning,":[104],"state":[106],"space,":[107],"actions":[108],"reward":[110],"functions":[111],"must":[112],"designed":[114],"carefully.":[115],"This":[116],"paper":[117],"presents":[118],"our":[119,131],"vision":[120],"different":[122],"layers":[123],"system,":[129],"effort":[132],"generating":[134],"tracking":[136],"both":[139],"using":[140,172],"(DRL).":[144],"The":[145],"experimental":[146],"results":[147],"show":[148],"compared":[150],"conventional":[152],"approaches,":[153],"learned":[155],"need":[158],"20%":[159],"less":[160,165,184,189],"18%":[164],"time":[166],"reach":[168],"target.":[170],"Furthermore,":[171],"policy":[175],"by":[177],"DRL,":[178],"58.14%":[183],"position":[185],"error":[186],"21.77%":[188],"power.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
