{"id":"https://openalex.org/W4402346038","doi":"https://doi.org/10.48550/arxiv.2407.12675","title":"Distilling Tiny and Ultra-fast Deep Neural Networks for Autonomous Navigation on Nano-UAVs","display_name":"Distilling Tiny and Ultra-fast Deep Neural Networks for Autonomous Navigation on Nano-UAVs","publication_year":2024,"publication_date":"2024-07-17","ids":{"openalex":"https://openalex.org/W4402346038","doi":"https://doi.org/10.48550/arxiv.2407.12675"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2407.12675","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.12675","pdf_url":"https://arxiv.org/pdf/2407.12675","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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.12675","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028966277","display_name":"Lorenzo Lamberti","orcid":"https://orcid.org/0000-0003-1659-618X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lamberti, Lorenzo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063919771","display_name":"Lorenzo Bellone","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bellone, Lorenzo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093777119","display_name":"Luka Macan","orcid":"https://orcid.org/0009-0007-6130-8841"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Macan, Luka","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013674490","display_name":"Enrico Natalizio","orcid":"https://orcid.org/0000-0001-8553-5722"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Natalizio, Enrico","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038717922","display_name":"Francesco Conti","orcid":"https://orcid.org/0000-0002-7924-933X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Conti, Francesco","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061890705","display_name":"Daniele Palossi","orcid":"https://orcid.org/0000-0003-4487-0836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Palossi, Daniele","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043408422","display_name":"Luca Benini","orcid":"https://orcid.org/0000-0001-8068-3806"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Benini, Luca","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5028966277"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.991100013256073,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.991100013256073,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9832000136375427,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.974399983882904,"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/nano","display_name":"Nano-","score":0.6084384322166443},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5759449005126953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4910929203033447},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4377059042453766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42211514711380005},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.3761635720729828},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.3554112911224365},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.28860217332839966},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.19959333539009094}],"concepts":[{"id":"https://openalex.org/C2780357685","wikidata":"https://www.wikidata.org/wiki/Q154357","display_name":"Nano-","level":2,"score":0.6084384322166443},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5759449005126953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4910929203033447},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4377059042453766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42211514711380005},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.3761635720729828},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.3554112911224365},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28860217332839966},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.19959333539009094},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2407.12675","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.12675","pdf_url":"https://arxiv.org/pdf/2407.12675","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2407.12675","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.12675","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.12675","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.12675","pdf_url":"https://arxiv.org/pdf/2407.12675","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":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4392633724","https://openalex.org/W2004288825","https://openalex.org/W4401380321","https://openalex.org/W2523793464","https://openalex.org/W2631168066","https://openalex.org/W3019877027","https://openalex.org/W4392541026","https://openalex.org/W4308484375","https://openalex.org/W4388045463","https://openalex.org/W2611032439"],"abstract_inverted_index":{"Nano-sized":[0],"unmanned":[1],"aerial":[2],"vehicles":[3],"(UAVs)":[4],"are":[5],"ideal":[6],"candidates":[7],"for":[8,121],"flying":[9],"Internet-of-Things":[10],"smart":[11],"sensors":[12],"to":[13,95,98,107],"collect":[14,111],"information":[15],"in":[16,60],"narrow":[17,165],"spaces.":[18],"This":[19],"requires":[20],"ultra-fast":[21],"navigation":[22,36],"under":[23],"very":[24],"tight":[25],"memory/computation":[26],"constraints.":[27],"The":[28],"PULP-Dronet":[29,134,186],"convolutional":[30],"neural":[31],"network":[32],"(CNN)":[33],"enables":[34],"autonomous":[35],"running":[37,139],"aboard":[38],"a":[39,48,79,112,128,141,153,157,164,169,173],"nano-UAV":[40],"at":[41,44,172],"19":[42],"frame/s,":[43],"the":[45,65,181,184],"cost":[46],"of":[47,52,68,82,105,132,163,177],"large":[49],"memory":[50,90],"footprint":[51,91],"320":[53],"kB":[54],"--":[55],"and":[56,71,125,135,159,168],"with":[57,84,152],"drone":[58],"control":[59],"complex":[61],"scenarios":[62],"hindered":[63],"by":[64,93],"disjoint":[66],"training":[67],"collision":[69],"avoidance":[70],"steering":[72],"capabilities.":[73],"In":[74,180],"this":[75],"work,":[76],"we":[77,110,126],"distill":[78],"novel":[80],"family":[81],"CNNs":[83,138],"better":[85],"capabilities":[86],"than":[87],"PULP-Dronet,":[88],"but":[89],"reduced":[92],"up":[94,106],"168x":[96,191],"(down":[97],"2.9":[99],"kB),":[100],"achieving":[101],"an":[102],"inference":[103],"rate":[104,156],"139":[108],"frame/s;":[109],"new":[113],"open-source":[114],"unified":[115],"collision/steering":[116],"66":[117],"k":[118],"images":[119],"dataset":[120],"more":[122,192],"robust":[123],"navigation;":[124],"perform":[127],"thorough":[129],"in-field":[130],"analysis":[131],"both":[133],"our":[136],"tiny":[137],"on":[140],"commercially":[142],"available":[143],"nano-UAV.":[144],"Our":[145],"tiniest":[146],"CNN,":[147],"called":[148],"Tiny-PULP-Dronet":[149],"v3,":[150],"navigates":[151],"100%":[154],"success":[155],"challenging":[158],"never-seen-before":[160],"path,":[161],"composed":[162],"obstacle-populated":[166],"corridor":[167],"180\u00b0":[170],"turn,":[171],"maximum":[174],"target":[175],"speed":[176],"0.5":[178],"m/s.":[179],"same":[182],"scenario,":[183],"SoA":[185],"consistently":[187],"fails":[188],"despite":[189],"having":[190],"parameters.":[193]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2024-09-09T00:00:00"}