{"id":"https://openalex.org/W3198728799","doi":"https://doi.org/10.1109/acirs52449.2021.9519318","title":"Simulated Data Generation through Algorithmic Force Coefficient Estimation for AI-Based Robotic Projectile Launch Modeling","display_name":"Simulated Data Generation through Algorithmic Force Coefficient Estimation for AI-Based Robotic Projectile Launch Modeling","publication_year":2021,"publication_date":"2021-07-16","ids":{"openalex":"https://openalex.org/W3198728799","doi":"https://doi.org/10.1109/acirs52449.2021.9519318","mag":"3198728799"},"language":"en","primary_location":{"id":"doi:10.1109/acirs52449.2021.9519318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acirs52449.2021.9519318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)","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/A5035137045","display_name":"Sajiv Shah","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136029","display_name":"Saratoga Hospital","ror":"https://ror.org/048j1wp71","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210136029"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sajiv Shah","raw_affiliation_strings":["Saratoga High School, Saratoga, California, USA"],"affiliations":[{"raw_affiliation_string":"Saratoga High School, Saratoga, California, USA","institution_ids":["https://openalex.org/I4210136029"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035149922","display_name":"Ayaan Haque","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136029","display_name":"Saratoga Hospital","ror":"https://ror.org/048j1wp71","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210136029"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ayaan Haque","raw_affiliation_strings":["Saratoga High School, Saratoga, California, USA"],"affiliations":[{"raw_affiliation_string":"Saratoga High School, Saratoga, California, USA","institution_ids":["https://openalex.org/I4210136029"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101783051","display_name":"Fei Liu","orcid":"https://orcid.org/0000-0003-0266-6896"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Liu","raw_affiliation_strings":["University of California San Diego, San Diego, California, USA"],"affiliations":[{"raw_affiliation_string":"University of California San Diego, San Diego, California, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035137045"],"corresponding_institution_ids":["https://openalex.org/I4210136029"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12089282,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10879","display_name":"Robotic Locomotion and Control","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10571","display_name":"Robotic Mechanisms and Dynamics","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/artificial-neural-network","display_name":"Artificial neural network","score":0.7361311316490173},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6871615052223206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6759402751922607},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5778776407241821},{"id":"https://openalex.org/keywords/projectile","display_name":"Projectile","score":0.5532019138336182},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4682985842227936},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4504847526550293},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4458424150943756},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4283148944377899},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4124000668525696},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34475576877593994},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08920267224311829}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7361311316490173},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6871615052223206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6759402751922607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5778776407241821},{"id":"https://openalex.org/C49304495","wikidata":"https://www.wikidata.org/wiki/Q49393","display_name":"Projectile","level":2,"score":0.5532019138336182},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4682985842227936},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4504847526550293},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4458424150943756},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4283148944377899},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4124000668525696},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34475576877593994},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08920267224311829},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acirs52449.2021.9519318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acirs52449.2021.9519318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1549749298","https://openalex.org/W1845972764","https://openalex.org/W1977655452","https://openalex.org/W2008026620","https://openalex.org/W2110139691","https://openalex.org/W2135708407","https://openalex.org/W2293363371","https://openalex.org/W2293480950","https://openalex.org/W2530849036","https://openalex.org/W2751586045","https://openalex.org/W2801984012","https://openalex.org/W2805869290","https://openalex.org/W2885397520","https://openalex.org/W2886076722","https://openalex.org/W2901496726","https://openalex.org/W2947976731","https://openalex.org/W2962730452","https://openalex.org/W2962940229","https://openalex.org/W2963092423","https://openalex.org/W2989904459","https://openalex.org/W3010993481","https://openalex.org/W3036207925","https://openalex.org/W3101007570","https://openalex.org/W3104397553","https://openalex.org/W3119933956","https://openalex.org/W3144490514","https://openalex.org/W3146773136","https://openalex.org/W3175849793","https://openalex.org/W3207878086","https://openalex.org/W4246394278","https://openalex.org/W4301501993","https://openalex.org/W6639175102","https://openalex.org/W6681588610","https://openalex.org/W6743666982","https://openalex.org/W6758539823","https://openalex.org/W6774822518","https://openalex.org/W6792806877"],"related_works":["https://openalex.org/W3134466133","https://openalex.org/W2362460327","https://openalex.org/W4401424305","https://openalex.org/W2943984654","https://openalex.org/W2883642900","https://openalex.org/W2330459747","https://openalex.org/W2074764239","https://openalex.org/W2365078747","https://openalex.org/W2903025760","https://openalex.org/W4289147272"],"abstract_inverted_index":{"Modeling":[0],"of":[1,13,18,39,42,107,112,137,157,195,206,214,226],"non-rigid":[2,161,196],"object":[3,44,162],"launching":[4],"and":[5,36,74,183,198,222],"manipulation":[6],"is":[7,47,56,79,242],"complex":[8],"considering":[9],"the":[10,37,40,43,101,120,135,138,212,224],"wide":[11],"range":[12],"dynamics":[14],"affecting":[15],"trajectory,":[16],"many":[17],"which":[19,164],"may":[20],"be":[21,27,125,166],"unknown.":[22],"Using":[23],"physics":[24,122],"models":[25,55,73,123],"can":[26,95,124,165],"inaccurate":[28],"because":[29],"they":[30,201],"cannot":[31],"account":[32,96],"for":[33,53,85,97,154,160,185,229],"unknown":[34],"factors":[35],"effects":[38],"deformation":[41],"as":[45,91],"it":[46],"launched;":[48],"moreover,":[49],"deriving":[50],"force":[51,118,158,219],"coefficients":[52,159],"these":[54],"not":[57],"possible":[58],"without":[59],"extensive":[60],"experimental":[61,108,209],"testing.":[62],"Recently,":[63],"advancements":[64],"in":[65,171],"data-powered":[66],"artificial":[67],"intelligence":[68],"methods":[69],"have":[70],"allowed":[71],"learnable":[72],"systems":[75],"to":[76,81,103,127,132,168,173,190],"emerge.":[77],"It":[78],"desirable":[80],"train":[82],"a":[83,89,151,179,204],"model":[84,192],"launch":[86,193],"prediction":[87],"on":[88],"robot,":[90],"deep":[92,113,187],"neural":[93,114,143,188,233],"networks":[94],"immeasurable":[98],"dynamics.":[99],"However,":[100],"inability":[102],"collect":[104],"large":[105,175],"amounts":[106],"data":[109,131,217,228],"decreases":[110],"performance":[111],"networks.":[115,144],"Through":[116],"estimating":[117],"coefficients,":[119],"accepted":[121],"leveraged":[126],"produce":[128],"adequate":[129],"supplemental":[130],"artificially":[133],"increase":[134],"size":[136],"training":[139,181,230],"set,":[140],"yielding":[141],"improved":[142],"In":[145],"this":[146],"paper,":[147],"we":[148],"introduce":[149],"FCE-NN,":[150],"new":[152],"framework":[153],"algorithmic":[155],"estimation":[156,221],"launching,":[163],"generalized":[167],"other":[169],"domains,":[170],"order":[172],"generate":[174],"datasets.":[176],"We":[177],"implement":[178],"novel":[180],"algorithm":[182],"objective":[184],"our":[186],"network":[189],"accurately":[191],"trajectory":[194],"objects":[197],"predict":[199],"whether":[200],"will":[202],"hit":[203],"series":[205],"targets.":[207],"Our":[208],"results":[210],"demonstrate":[211],"effectiveness":[213],"using":[215],"simulated":[216,227],"from":[218],"coefficient":[220],"shows":[223],"importance":[225],"an":[231],"effective":[232],"network.":[234],"<sup":[235,238],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[236,239],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[237,240],"Code":[241],"available":[243],"at":[244],"https:/igithub.com/ayaanzhaque/FCE-NN":[245]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}