{"id":"https://openalex.org/W4206927556","doi":"https://doi.org/10.1109/ssci50451.2021.9659907","title":"Investigating Neural Network Architectures, Techniques, and Datasets for Autonomous Navigation in Simulation","display_name":"Investigating Neural Network Architectures, Techniques, and Datasets for Autonomous Navigation in Simulation","publication_year":2021,"publication_date":"2021-12-05","ids":{"openalex":"https://openalex.org/W4206927556","doi":"https://doi.org/10.1109/ssci50451.2021.9659907"},"language":"en","primary_location":{"id":"doi:10.1109/ssci50451.2021.9659907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci50451.2021.9659907","pdf_url":null,"source":{"id":"https://openalex.org/S4363604921","display_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5112751478","display_name":"Oliver Chang","orcid":"https://orcid.org/0000-0002-1984-9552"},"institutions":[{"id":"https://openalex.org/I177881444","display_name":"Pomona College","ror":"https://ror.org/0074grg94","country_code":"US","type":"education","lineage":["https://openalex.org/I177881444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oliver Chang","raw_affiliation_strings":["Pomona College, Claremont, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pomona College, Claremont, California, USA","institution_ids":["https://openalex.org/I177881444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081529692","display_name":"Christiana Marchese","orcid":null},"institutions":[{"id":"https://openalex.org/I177881444","display_name":"Pomona College","ror":"https://ror.org/0074grg94","country_code":"US","type":"education","lineage":["https://openalex.org/I177881444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christiana Marchese","raw_affiliation_strings":["Pomona College, Claremont, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pomona College, Claremont, California, USA","institution_ids":["https://openalex.org/I177881444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083449091","display_name":"Jared Mejia","orcid":null},"institutions":[{"id":"https://openalex.org/I177881444","display_name":"Pomona College","ror":"https://ror.org/0074grg94","country_code":"US","type":"education","lineage":["https://openalex.org/I177881444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jared Mejia","raw_affiliation_strings":["Pomona College, Claremont, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pomona College, Claremont, California, USA","institution_ids":["https://openalex.org/I177881444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070428667","display_name":"Anthony J. Clark","orcid":"https://orcid.org/0000-0001-8196-8889"},"institutions":[{"id":"https://openalex.org/I177881444","display_name":"Pomona College","ror":"https://ror.org/0074grg94","country_code":"US","type":"education","lineage":["https://openalex.org/I177881444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anthony J. Clark","raw_affiliation_strings":["Pomona College, Claremont, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pomona College, Claremont, California, USA","institution_ids":["https://openalex.org/I177881444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177881444"],"apc_list":null,"apc_paid":null,"fwci":0.0656,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.38681948,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9977999925613403,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9918000102043152,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8407713770866394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6768898367881775},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6301289796829224},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5934263467788696},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5125800967216492},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5077722668647766},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4924350678920746},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46358275413513184},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.44272568821907043},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.43349990248680115},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4181009531021118},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.41063880920410156},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18879440426826477}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8407713770866394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6768898367881775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6301289796829224},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5934263467788696},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5125800967216492},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5077722668647766},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4924350678920746},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46358275413513184},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.44272568821907043},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.43349990248680115},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4181009531021118},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.41063880920410156},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18879440426826477},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci50451.2021.9659907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci50451.2021.9659907","pdf_url":null,"source":{"id":"https://openalex.org/S4363604921","display_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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":29,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1686810756","https://openalex.org/W2163605009","https://openalex.org/W2167340365","https://openalex.org/W2218761850","https://openalex.org/W2734960757","https://openalex.org/W2793310003","https://openalex.org/W2794712769","https://openalex.org/W2891790128","https://openalex.org/W2893813411","https://openalex.org/W2909953480","https://openalex.org/W2963390419","https://openalex.org/W2963446712","https://openalex.org/W2963855133","https://openalex.org/W2996666233","https://openalex.org/W2999067824","https://openalex.org/W3006436762","https://openalex.org/W3023427029","https://openalex.org/W3029192705","https://openalex.org/W3044499041","https://openalex.org/W3091160449","https://openalex.org/W3098350627","https://openalex.org/W3098490553","https://openalex.org/W3108691183","https://openalex.org/W3205596388","https://openalex.org/W4295719664","https://openalex.org/W6684191040","https://openalex.org/W6759886010","https://openalex.org/W6771756728"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W1508899372","https://openalex.org/W2012658348","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Neural":[0],"networks":[1],"(NNs)":[2],"are":[3],"becoming":[4],"an":[5,149,181],"increasingly":[6],"important":[7],"part":[8],"of":[9,38,42,71,84,97,130,186],"mobile":[10],"robot":[11],"control":[12],"systems.":[13],"Compared":[14],"with":[15,111,215],"traditional":[16],"methods,":[17],"NNs":[18],"(and":[19],"other":[20],"data-driven":[21],"techniques)":[22],"produce":[23],"comparable-if":[24],"not":[25],"better-results":[26],"while":[27],"requiring":[28],"less":[29],"engineering":[30],"knowhow.":[31],"Training":[32,115],"NNs,":[33,165,167],"however,":[34],"still":[35],"requires":[36],"exploration":[37],"a":[39,53,69,94,112,127,199,213,237],"significant":[40,128],"number":[41,96],"architectural,":[43],"optimization,":[44],"and":[45,73,79,168,243],"evaluation":[46],"options.":[47],"In":[48,203],"this":[49],"study,":[50],"we":[51,102],"build":[52],"simulation":[54,194],"environment,":[55],"generate":[56],"three":[57],"image":[58],"datasets":[59,116],"using":[60,68],"distinct":[61],"techniques,":[62],"train":[63],"652":[64],"models":[65,122,139,156,177],"(including":[66],"replicates)":[67],"variety":[70],"architectures":[72,170],"paradigms":[74],"(e.g.,":[75],"classification,":[76],"regression,":[77],"etc.),":[78],"evaluate":[80],"the":[81,85,105,119,152,184,187,193,223,227],"navigation":[82],"ability":[83],"model":[86,98,214],"in":[87,151,180,198],"simulation.":[88],"Our":[89],"goal":[90],"is":[91,196,207],"to":[92,118],"explore":[93],"large":[95],"possibilities":[99],"so":[100],"that":[101,125,212,232],"can":[103,234],"select":[104],"most":[106,137],"promising":[107,138],"for":[108,210],"future":[109],"study":[110],"physical":[113],"device.":[114],"leading":[117],"best":[120],"performing":[121],"were":[123,146],"those":[124],"included":[126,147],"amount":[129],"noise":[131],"from":[132],"seemingly":[133,200],"inefficient":[134],"actions.":[135],"The":[136],"explicitly":[140],"incorporated":[141],"\u201cmemory\u201d":[142],"wherein":[143],"previous":[144],"actions":[145],"as":[148,158],"input":[150],"next":[153],"step.":[154],"Such":[155],"performed":[157],"good":[159,216],"or":[160],"better":[161],"than":[162],"conventional":[163],"convolutional":[164],"recurrent":[166],"custom":[169],"including":[171],"two":[172],"camera":[173],"frames.":[174],"Although":[175],"trained":[176],"perform":[178,220],"well":[179,221],"environment":[182,195],"matching":[183],"distribution":[185],"training":[188],"dataset,":[189],"they":[190],"fail":[191],"when":[192],"altered":[197],"insignificant":[201],"manner.":[202],"robotics":[204],"research":[205],"it":[206],"often":[208,235],"taken":[209],"granted":[211],"validation":[217,241],"characteristics":[218],"will":[219],"on":[222],"underlying":[224],"task,":[225],"but":[226],"results":[228],"presented":[229],"here":[230],"show":[231],"there":[233],"be":[236],"loose":[238],"relationship":[239],"between":[240],"metrics":[242],"performance.":[244]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}