{"id":"https://openalex.org/W4282009277","doi":"https://doi.org/10.1109/eais51927.2022.9787735","title":"Collision-Free Navigation using Evolutionary Symmetrical Neural Networks","display_name":"Collision-Free Navigation using Evolutionary Symmetrical Neural Networks","publication_year":2022,"publication_date":"2022-05-25","ids":{"openalex":"https://openalex.org/W4282009277","doi":"https://doi.org/10.1109/eais51927.2022.9787735"},"language":"en","primary_location":{"id":"doi:10.1109/eais51927.2022.9787735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eais51927.2022.9787735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","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/A5083360810","display_name":"Hesham M. Eraqi","orcid":"https://orcid.org/0000-0001-9430-7553"},"institutions":[{"id":"https://openalex.org/I80693520","display_name":"American University in Cairo","ror":"https://ror.org/0176yqn58","country_code":"EG","type":"education","lineage":["https://openalex.org/I80693520"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Hesham M. Eraqi","raw_affiliation_strings":["The American University in Cairo,Department of Computer Science,New Cairo,Egypt","Department of Computer Science, The American University in Cairo, New Cairo, Egypt"],"affiliations":[{"raw_affiliation_string":"The American University in Cairo,Department of Computer Science,New Cairo,Egypt","institution_ids":["https://openalex.org/I80693520"]},{"raw_affiliation_string":"Department of Computer Science, The American University in Cairo, New Cairo, Egypt","institution_ids":["https://openalex.org/I80693520"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022973127","display_name":"Mena Nagiub","orcid":"https://orcid.org/0000-0001-5375-9510"},"institutions":[{"id":"https://openalex.org/I4210112099","display_name":"Valeo (Germany)","ror":"https://ror.org/01zkeq752","country_code":"DE","type":"company","lineage":["https://openalex.org/I220619192","https://openalex.org/I4210112099"]},{"id":"https://openalex.org/I4210103324","display_name":"Fachverband Geb\u00e4ude-Klima (Germany)","ror":"https://ror.org/01dc86h50","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210103324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mena Nagiub","raw_affiliation_strings":["Valeo Schalter und Sensoren GmbH,Bietigheim-Bissingen,Germany","Valeo Schalter und Sensoren GmbH, Bietigheim-Bissingen, Germany"],"affiliations":[{"raw_affiliation_string":"Valeo Schalter und Sensoren GmbH,Bietigheim-Bissingen,Germany","institution_ids":["https://openalex.org/I4210103324"]},{"raw_affiliation_string":"Valeo Schalter und Sensoren GmbH, Bietigheim-Bissingen, Germany","institution_ids":["https://openalex.org/I4210112099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080839415","display_name":"Peter Sidra","orcid":null},"institutions":[{"id":"https://openalex.org/I80693520","display_name":"American University in Cairo","ror":"https://ror.org/0176yqn58","country_code":"EG","type":"education","lineage":["https://openalex.org/I80693520"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Peter Sidra","raw_affiliation_strings":["The American University in Cairo,Department of Computer Science,New Cairo,Egypt","Department of Computer Science, The American University in Cairo, New Cairo, Egypt"],"affiliations":[{"raw_affiliation_string":"The American University in Cairo,Department of Computer Science,New Cairo,Egypt","institution_ids":["https://openalex.org/I80693520"]},{"raw_affiliation_string":"Department of Computer Science, The American University in Cairo, New Cairo, Egypt","institution_ids":["https://openalex.org/I80693520"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083360810"],"corresponding_institution_ids":["https://openalex.org/I80693520"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04496832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":1.0,"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":1.0,"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":0.998199999332428,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.6543641090393066},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5495967268943787},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.45028525590896606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42116886377334595},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09260150790214539}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6543641090393066},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5495967268943787},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.45028525590896606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42116886377334595},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09260150790214539}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eais51927.2022.9787735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eais51927.2022.9787735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1598952354","https://openalex.org/W1966991711","https://openalex.org/W2118916601","https://openalex.org/W2126321580","https://openalex.org/W2529646329","https://openalex.org/W2886427086","https://openalex.org/W3036285418","https://openalex.org/W3045686492","https://openalex.org/W3130640781","https://openalex.org/W3160536906","https://openalex.org/W6635959259"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W3113932901","https://openalex.org/W4396701345","https://openalex.org/W650625605","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Collision":[0],"avoidance":[1],"systems":[2],"play":[3],"a":[4,35,86],"vital":[5],"role":[6],"in":[7,112],"reducing":[8],"the":[9,21,47,54,59,71,90,101,122,125,132,143,146,153,158,168,178,184],"number":[10,179],"of":[11,70,124,135,145,180],"vehicle":[12,72],"accidents":[13],"and":[14,64,79,104,129,165],"saving":[15],"human":[16],"lives.":[17],"This":[18],"paper":[19],"extends":[20],"previous":[22],"work":[23],"using":[24,85],"evolutionary":[25],"neural":[26,42],"networks":[27],"for":[28,74,162,183],"reactive":[29,136],"collision":[30,137],"avoidance.":[31,138],"We":[32],"are":[33,82,97,151],"proposing":[34],"new":[36,169],"method":[37,45,103,109,155],"we":[38,119,140],"have":[39,120,141],"called":[40],"symmetric":[41],"networks.":[43],"The":[44,77,108,149],"improves":[46],"model\u2019s":[48,159],"performance":[49],"by":[50],"enforcing":[51],"constraints":[52],"between":[53],"network":[55],"weights":[56,174],"which":[57],"reduces":[58],"model":[60],"optimization":[61],"search":[62],"space":[63],"hence,":[65],"learns":[66],"more":[67],"accurate":[68],"control":[69],"steering":[73],"improved":[75,157,177],"maneuvering.":[76],"training":[78,163],"validation":[80],"processes":[81],"carried":[83],"out":[84],"simulation":[87],"environment":[88],"-":[89],"codebase":[91],"is":[92,110],"publicly":[93],"available.":[94],"Extensive":[95],"experiments":[96],"conducted":[98],"to":[99,167],"analyze":[100],"proposed":[102,147,154],"evaluate":[105],"its":[106],"performance.":[107],"tested":[111,142],"several":[113],"simulated":[114],"driving":[115],"scenarios.":[116,171],"In":[117],"addition,":[118],"analyzed":[121],"effect":[123],"rangefinder":[126],"sensor":[127],"resolution":[128],"noise":[130],"on":[131],"overall":[133],"goal":[134],"Finally,":[139],"generalization":[144,166],"method.":[148],"results":[150],"encouraging;":[152],"has":[156,175],"learning":[160],"curve":[161],"scenarios":[164],"test":[170],"Using":[172],"constrained":[173],"significantly":[176],"generations":[181],"required":[182],"Genetic":[185],"Algorithm":[186],"optimization.":[187]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
