{"id":"https://openalex.org/W2609009256","doi":"https://doi.org/10.1109/iros.2017.8206247","title":"Learning to fly by crashing","display_name":"Learning to fly by crashing","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2609009256","doi":"https://doi.org/10.1109/iros.2017.8206247","mag":"2609009256"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2017.8206247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8206247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5085397193","display_name":"Dhiraj Gandhi","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dhiraj Gandhi","raw_affiliation_strings":["The Robotics Institute, Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"The Robotics Institute, Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103895643","display_name":"Lerrel Pinto","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lerrel Pinto","raw_affiliation_strings":["The Robotics Institute, Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"The Robotics Institute, Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101761266","display_name":"Abhinav Gupta","orcid":"https://orcid.org/0000-0002-3646-2421"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhinav Gupta","raw_affiliation_strings":["The Robotics Institute, Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"The Robotics Institute, Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085397193"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":10.0125,"has_fulltext":false,"cited_by_count":252,"citation_normalized_percentile":{"value":0.98786694,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3948","last_page":"3955"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9988999962806702,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9876000285148621,"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/drone","display_name":"Drone","score":0.8811550736427307},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8636081218719482},{"id":"https://openalex.org/keywords/crash","display_name":"Crash","score":0.8415048122406006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7885698080062866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5443496108055115},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48811087012290955},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.44513165950775146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3587559759616852}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.8811550736427307},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8636081218719482},{"id":"https://openalex.org/C183469790","wikidata":"https://www.wikidata.org/wiki/Q333501","display_name":"Crash","level":2,"score":0.8415048122406006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7885698080062866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443496108055115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48811087012290955},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.44513165950775146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3587559759616852},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"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/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2017.8206247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8206247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1551338782","https://openalex.org/W1977464512","https://openalex.org/W1980969546","https://openalex.org/W1989125340","https://openalex.org/W2019586060","https://openalex.org/W2087387266","https://openalex.org/W2098251717","https://openalex.org/W2098836126","https://openalex.org/W2102605133","https://openalex.org/W2104154890","https://openalex.org/W2114384289","https://openalex.org/W2120682965","https://openalex.org/W2145339207","https://openalex.org/W2146071867","https://openalex.org/W2148820580","https://openalex.org/W2151290401","https://openalex.org/W2163605009","https://openalex.org/W2171740948","https://openalex.org/W2201912979","https://openalex.org/W2566792288","https://openalex.org/W2951234442","https://openalex.org/W2962736495","https://openalex.org/W2962887844","https://openalex.org/W2962957005","https://openalex.org/W2963516811","https://openalex.org/W2964112890","https://openalex.org/W2964335674","https://openalex.org/W6681644751","https://openalex.org/W6682324061","https://openalex.org/W6684191040","https://openalex.org/W6685261749","https://openalex.org/W6697071109"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4229448053","https://openalex.org/W4281702477","https://openalex.org/W2059768187","https://openalex.org/W2989932438","https://openalex.org/W4387297750","https://openalex.org/W2186333919"],"abstract_inverted_index":{"How":[0],"do":[1],"you":[2],"learn":[3,155],"to":[4,17,32,42,78,97,116,154],"navigate":[5],"an":[6],"Unmanned":[7],"Aerial":[8],"Vehicle":[9],"(UAV)":[10],"and":[11,50,82,105],"avoid":[12],"obstacles?":[13],"One":[14],"approach":[15],"is":[16,41,68,96,171],"use":[18,43,138],"a":[19,84,91,133,156],"small":[20],"dataset":[21,85,126],"collected":[22],"by":[23],"human":[24],"experts:":[25],"however,":[26],"high":[27],"capacity":[28],"learning":[29],"algorithms":[30],"tend":[31],"overfit":[33],"when":[34],"trained":[35],"with":[36,146,183],"little":[37],"data.":[38],"An":[39],"alternative":[40],"simulation.":[44],"But":[45],"the":[46,69,80,120,128,151,176],"gap":[47],"between":[48],"simulation":[49],"real":[51,66],"world":[52],"remains":[53],"large":[54],"especially":[55],"for":[56,161],"perception":[57],"problems.":[58],"The":[59],"reason":[60],"most":[61],"research":[62],"avoids":[63],"using":[64],"large-scale":[65],"data":[67,143,148],"fear":[70],"of":[71,86,119],"crashes!":[72],"In":[73],"this":[74,140,167],"paper,":[75],"we":[76],"propose":[77],"bite":[79],"bullet":[81],"collect":[83],"crashes":[87,106],"itself!":[88],"We":[89,110,137,164],"build":[90],"drone":[92,113],"whose":[93],"sole":[94],"purpose":[95],"crash":[98,111,123],"into":[99,107],"objects:":[100],"it":[101],"samples":[102],"naive":[103],"trajectories":[104,153],"random":[108],"objects.":[109],"our":[112],"11,500":[114],"times":[115],"create":[117],"one":[118],"biggest":[121],"UAV":[122,134,162,177],"dataset.":[124],"This":[125],"captures":[127],"different":[129],"ways":[130],"in":[131,144,174,179],"which":[132],"can":[135],"crash.":[136],"all":[139],"negative":[141],"flying":[142],"conjunction":[145],"positive":[147],"sampled":[149],"from":[150],"same":[152],"simple":[157,168],"yet":[158],"powerful":[159],"policy":[160],"navigation.":[163],"show":[165],"that":[166],"self-supervised":[169],"model":[170],"quite":[172],"effective":[173],"navigating":[175],"even":[178],"extremely":[180],"cluttered":[181],"environments":[182],"dynamic":[184],"obstacles":[185],"including":[186],"humans.":[187],"For":[188],"supplementary":[189],"video":[190],"see:.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":53},{"year":2020,"cited_by_count":35},{"year":2019,"cited_by_count":51},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":3}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}