{"id":"https://openalex.org/W3176767240","doi":"https://doi.org/10.5220/0010621400003061","title":"Generating Synthetic Training Data for Deep Learning-based UAV Trajectory Prediction","display_name":"Generating Synthetic Training Data for Deep Learning-based UAV Trajectory Prediction","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3176767240","doi":"https://doi.org/10.5220/0010621400003061","mag":"3176767240"},"language":"en","primary_location":{"id":"doi:10.5220/0010621400003061","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0010621400003061","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Robotics, Computer Vision and Intelligent Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0010621400003061","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Stefan Becker","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Stefan Becker","raw_affiliation_strings":["Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ronny Hug","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ronny Hug","raw_affiliation_strings":["Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wolfgang Huebner","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Huebner","raw_affiliation_strings":["Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Michael Arens","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Arens","raw_affiliation_strings":["Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Ettlingen, Germany, --- Select a Country ---","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"last","author":{"id":null,"display_name":"Brendan Morris","orcid":null},"institutions":[{"id":"https://openalex.org/I133999245","display_name":"University of Nevada, Las Vegas","ror":"https://ror.org/0406gha72","country_code":"US","type":"education","lineage":["https://openalex.org/I133999245"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brendan Morris","raw_affiliation_strings":["University of Nevada, Las Vegas, U.S.A., --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"University of Nevada, Las Vegas, U.S.A., --- Select a Country ---","institution_ids":["https://openalex.org/I133999245"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210111500"],"apc_list":null,"apc_paid":null,"fwci":0.6511,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.68315337,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9965000152587891,"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":0.9760000109672546,"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/trajectory","display_name":"Trajectory","score":0.8410000205039978},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5928999781608582},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5412999987602234},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5254999995231628},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.5185999870300293},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4812999963760376},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.46380001306533813},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4546999931335449}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8410000205039978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7184000015258789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.671999990940094},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5928999781608582},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5254999995231628},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.5185999870300293},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4812999963760376},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.46380001306533813},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.454800009727478},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4546999931335449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4327000081539154},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2919999957084656},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25999999046325684}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.5220/0010621400003061","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0010621400003061","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Robotics, Computer Vision and Intelligent Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2107.00422","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.00422","pdf_url":"https://arxiv.org/pdf/2107.00422","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:fraunhofer.de:N-642686","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-642686.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IOSB","raw_type":"Conference Paper"},{"id":"pmh:oai:null:publica/412771","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/412771","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference paper"},{"id":"pmh:oai:oasis.library.unlv.edu:ece_fac_articles-2112","is_oa":false,"landing_page_url":"https://oasis.library.unlv.edu/ece_fac_articles/1109","pdf_url":null,"source":{"id":"https://openalex.org/S4377196371","display_name":"Digital Scholarship - UNLV (University of Nevada Reno)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I134113660","host_organization_name":"University of Nevada, Reno","host_organization_lineage":["https://openalex.org/I134113660"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical & Computer Engineering Faculty Research","raw_type":"article"},{"id":"pmh:oai:oasis.library.unlv.edu:ece_fac_articles-2113","is_oa":false,"landing_page_url":"https://oasis.library.unlv.edu/ece_fac_articles/1110","pdf_url":null,"source":{"id":"https://openalex.org/S4377196371","display_name":"Digital Scholarship - UNLV (University of Nevada Reno)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I134113660","host_organization_name":"University of Nevada, Reno","host_organization_lineage":["https://openalex.org/I134113660"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical & Computer Engineering Faculty Research","raw_type":"article"}],"best_oa_location":{"id":"doi:10.5220/0010621400003061","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0010621400003061","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Robotics, Computer Vision and Intelligent Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning-based":[1],"models,":[2],"such":[3],"as":[4],"recurrent":[5],"neural":[6],"networks":[7],"(RNNs),":[8],"have":[9],"been":[10],"applied":[11],"to":[12,111,127,148],"various":[13],"sequence":[14,133],"learning":[15],"tasks":[16],"with":[17,47],"great":[18],"success.":[19],"Following":[20],"this,":[21],"these":[22,40,139],"models":[23,41,184],"are":[24,91,143],"increasingly":[25],"replacing":[26],"classic":[27,182],"approaches":[28],"in":[29,83],"object":[30,45],"tracking":[31,189],"applications":[32],"for":[33,65,75,119,145],"motion":[34],"prediction.":[35],"On":[36],"the":[37,53,101,160,163,177,196],"one":[38],"hand,":[39,55],"can":[42,95,124,180],"capture":[43],"complex":[44],"dynamics":[46],"less":[48],"modeling":[49],"required,":[50],"but":[51],"on":[52,58,176,185,195],"other":[54],"they":[56,94],"depend":[57],"a":[59,107,112,132,151,186],"large":[60],"amount":[61],"of":[62,80,115,134,162],"training":[63],"data":[64,79,154,179],"parameter":[66],"tuning.":[67],"Towards":[68],"this":[69],"end,":[70],"we":[71,167],"present":[72],"an":[73,170],"approach":[74],"generating":[76],"synthetic":[77,164],"trajectory":[78,153,165],"unmanned-aerial-vehicles":[81],"(UAVs)":[82],"image":[84,149],"space.":[85],"Since":[86],"UAVs,":[87],"or":[88],"rather":[89],"quadrotors":[90,122],"dynamical":[92],"systems,":[93],"not":[96],"follow":[97],"arbitrary":[98],"trajectories.":[99],"With":[100],"prerequisite":[102],"that":[103,169],"UAV":[104,188],"trajectories":[105,130],"fulfill":[106],"smoothness":[108],"criterion":[109],"corresponding":[110],"minimal":[113],"change":[114],"higher-order":[116],"motion,":[117],"methods":[118],"planning":[120],"aggressive":[121],"flights":[123],"be":[125],"utilized":[126],"generate":[128],"optimal":[129],"through":[131],"3D":[135],"waypoints.":[136],"By":[137],"projecting":[138],"maneuver":[140],"trajectories,":[141],"which":[142],"suitable":[144],"controlling":[146],"quadrotors,":[147],"space,":[150],"versatile":[152],"set":[155],"is":[156,193],"realized.":[157],"To":[158],"demonstrate":[159],"applicability":[161],"data,":[166],"show":[168],"RNN-based":[171],"prediction":[172],"model":[173],"solely":[174],"trained":[175],"generated":[178],"outperform":[181],"reference":[183],"real-world":[187],"dataset.":[190,200],"The":[191],"evaluation":[192],"done":[194],"publicly":[197],"available":[198],"ANTI-UAV":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2021-07-05T00:00:00"}
