{"id":"https://openalex.org/W4200631628","doi":"https://doi.org/10.1109/ccnc49033.2022.9700609","title":"Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU","display_name":"Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU","publication_year":2022,"publication_date":"2022-01-08","ids":{"openalex":"https://openalex.org/W4200631628","doi":"https://doi.org/10.1109/ccnc49033.2022.9700609"},"language":"en","primary_location":{"id":"doi:10.1109/ccnc49033.2022.9700609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc49033.2022.9700609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)","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/A5083993857","display_name":"Nicholas Polosky","orcid":null},"institutions":[{"id":"https://openalex.org/I2801039369","display_name":"Marconi University","ror":"https://ror.org/00j0rk173","country_code":"IT","type":"education","lineage":["https://openalex.org/I2801039369"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicholas Polosky","raw_affiliation_strings":["ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","institution_ids":["https://openalex.org/I2801039369"]},{"raw_affiliation_string":"Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081648835","display_name":"Tyler Gwin","orcid":null},"institutions":[{"id":"https://openalex.org/I2801039369","display_name":"Marconi University","ror":"https://ror.org/00j0rk173","country_code":"IT","type":"education","lineage":["https://openalex.org/I2801039369"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Tyler Gwin","raw_affiliation_strings":["ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","institution_ids":["https://openalex.org/I2801039369"]},{"raw_affiliation_string":"Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028225787","display_name":"Sean Furman","orcid":null},"institutions":[{"id":"https://openalex.org/I2801039369","display_name":"Marconi University","ror":"https://ror.org/00j0rk173","country_code":"IT","type":"education","lineage":["https://openalex.org/I2801039369"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sean Furman","raw_affiliation_strings":["ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","institution_ids":["https://openalex.org/I2801039369"]},{"raw_affiliation_string":"Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073487095","display_name":"Parth Barhanpurkar","orcid":null},"institutions":[{"id":"https://openalex.org/I2801039369","display_name":"Marconi University","ror":"https://ror.org/00j0rk173","country_code":"IT","type":"education","lineage":["https://openalex.org/I2801039369"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Parth Barhanpurkar","raw_affiliation_strings":["ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","institution_ids":["https://openalex.org/I2801039369"]},{"raw_affiliation_string":"Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068413452","display_name":"Jithin Jagannath","orcid":"https://orcid.org/0000-0002-4059-6481"},"institutions":[{"id":"https://openalex.org/I2801039369","display_name":"Marconi University","ror":"https://ror.org/00j0rk173","country_code":"IT","type":"education","lineage":["https://openalex.org/I2801039369"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Jithin Jagannath","raw_affiliation_strings":["ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANDRO Computational Solutions, LLC,Marconi-Rosenblatt AI/ML Innovation Lab,Rome,NY","institution_ids":["https://openalex.org/I2801039369"]},{"raw_affiliation_string":"Marconi-Rosenblatt AI/ML Innovation Lab, ANDRO Computational Solutions, LLC, Rome, NY","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2801039369"],"apc_list":null,"apc_paid":null,"fwci":0.6056,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.62753054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9991999864578247,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9951000213623047,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.8292909264564514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.757495105266571},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.42365503311157227},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3842652440071106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3425511419773102},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.33782196044921875},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.07612860202789307}],"concepts":[{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.8292909264564514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.757495105266571},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.42365503311157227},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3842652440071106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3425511419773102},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.33782196044921875},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.07612860202789307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccnc49033.2022.9700609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc49033.2022.9700609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)","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":25,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1999244633","https://openalex.org/W2117228865","https://openalex.org/W2520707372","https://openalex.org/W2962865553","https://openalex.org/W2982095652","https://openalex.org/W3011144238","https://openalex.org/W3043971245","https://openalex.org/W3081167590","https://openalex.org/W3084000032","https://openalex.org/W3116474649","https://openalex.org/W3125913093","https://openalex.org/W3148176530","https://openalex.org/W3176084020","https://openalex.org/W3181605115","https://openalex.org/W4214520160","https://openalex.org/W4288083516","https://openalex.org/W6677308130","https://openalex.org/W6752941136","https://openalex.org/W6769227165","https://openalex.org/W6774815639","https://openalex.org/W6779611811","https://openalex.org/W6782298681","https://openalex.org/W6789544141","https://openalex.org/W6801009340"],"related_works":["https://openalex.org/W4317634134","https://openalex.org/W2981729160","https://openalex.org/W4310743282","https://openalex.org/W2743212448","https://openalex.org/W2889566344","https://openalex.org/W3113932901","https://openalex.org/W1819938260","https://openalex.org/W2340892746","https://openalex.org/W3163022373","https://openalex.org/W3005999311"],"abstract_inverted_index":{"Interest":[0],"in":[1,101,168,174],"unmanned":[2],"aerial":[3],"system":[4],"(UAS)":[5],"powered":[6],"solutions":[7],"for":[8,47,64,166],"6G":[9,78,175],"communication":[10,170,176],"networks":[11],"has":[12],"grown":[13],"immensely":[14],"with":[15,88],"the":[16,36,85,118],"widespread":[17],"availability":[18],"of":[19,38,149],"machine":[20,89,132],"learning":[21,90],"based":[22,91],"autonomy":[23,45,93],"modules":[24],"and":[25,52,69,108,143,183],"embedded":[26],"graphical":[27],"processing":[28],"units":[29],"(GPUs).":[30],"While":[31],"these":[32,113,158],"technologies":[33],"have":[34,123],"revolutionized":[35],"possibilities":[37],"UAS":[39,48,65,92],"solutions,":[40],"designing":[41],"an":[42],"operable,":[43],"robust":[44],"framework":[46,63],"remains":[49],"a":[50,145,164],"multi-faceted":[51],"difficult":[53],"problem.":[54],"In":[55],"this":[56],"work,":[57],"we":[58,99,116,122],"present":[59,144],"our":[60,130],"novel,":[61],"modular":[62],"autonomy,":[66],"entitled":[67],"MR-iFLY,":[68],"discuss":[70],"how":[71,103,129],"it":[72],"may":[73],"be":[74],"extended":[75],"to":[76,125,137],"enable":[77],"swarm":[79],"solutions.":[80],"We":[81,155],"begin":[82],"by":[83,178],"detailing":[84],"challenges":[86],"associated":[87],"on":[94],"resource":[95],"constrained":[96],"devices.":[97],"Next,":[98],"describe":[100,117],"depth,":[102],"MR-iFLY\u2019s":[104,150],"novel":[105],"depth":[106],"estimation":[107],"collision":[109,152,181],"avoidance":[110,153,182],"technology":[111],"meets":[112],"challenges.":[114],"Lastly,":[115],"various":[119],"evaluation":[120],"criteria":[121],"used":[124],"measure":[126],"performance,":[127],"show":[128],"optimized":[131],"vision":[133],"components":[134],"provide":[135],"up":[136],"15X":[138],"speedup":[139],"over":[140],"baseline":[141],"models":[142],"flight":[146],"demonstration":[147],"video":[148],"vision-based":[151],"technology.":[154],"argue":[156],"that":[157],"empirical":[159],"results":[160],"substantiate":[161],"MR-iFLY":[162],"as":[163],"candidate":[165],"use":[167],"reducing":[169],"overhead":[171],"between":[172],"nodes":[173],"swarms":[177],"providing":[179],"standalone":[180],"navigation":[184],"capabilities.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}