{"id":"https://openalex.org/W2969015047","doi":"https://doi.org/10.1109/icra.2019.8793688","title":"Learning Primitive Skills for Mobile Robots","display_name":"Learning Primitive Skills for Mobile Robots","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2969015047","doi":"https://doi.org/10.1109/icra.2019.8793688","mag":"2969015047"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2019.8793688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2019.8793688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Robotics and Automation (ICRA)","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/A5101638641","display_name":"Yifeng Zhu","orcid":"https://orcid.org/0000-0002-2290-1411"},"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":"Yifeng Zhu","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005267157","display_name":"Devin Schwab","orcid":"https://orcid.org/0000-0003-0172-9744"},"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":"Devin Schwab","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088276691","display_name":"Manuela Veloso","orcid":"https://orcid.org/0000-0001-6738-238X"},"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":"Manuela Veloso","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101638641"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.8401,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80331018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"7597","last_page":"7603"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9987999796867371,"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/T10533","display_name":"Teaching and Learning Programming","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.6909465193748474},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.6403073072433472},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5363814234733582},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5179592370986938},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.32969576120376587},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3185955286026001}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6909465193748474},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.6403073072433472},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5363814234733582},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5179592370986938},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.32969576120376587},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3185955286026001}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2019.8793688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2019.8793688","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Robotics and Automation (ICRA)","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":45,"referenced_works":["https://openalex.org/W1506497862","https://openalex.org/W1516054196","https://openalex.org/W1554570365","https://openalex.org/W1579667258","https://openalex.org/W1757796397","https://openalex.org/W1771410628","https://openalex.org/W2057861900","https://openalex.org/W2097437030","https://openalex.org/W2127412976","https://openalex.org/W2145339207","https://openalex.org/W2169659168","https://openalex.org/W2173248099","https://openalex.org/W2257979135","https://openalex.org/W2336687883","https://openalex.org/W2513603937","https://openalex.org/W2575302769","https://openalex.org/W2594103415","https://openalex.org/W2736601468","https://openalex.org/W2741122588","https://openalex.org/W2766447205","https://openalex.org/W2808414353","https://openalex.org/W2949561945","https://openalex.org/W2952629144","https://openalex.org/W2963184939","https://openalex.org/W2963616477","https://openalex.org/W2963864421","https://openalex.org/W2964043796","https://openalex.org/W4298857966","https://openalex.org/W4324106947","https://openalex.org/W6630231469","https://openalex.org/W6631014299","https://openalex.org/W6634638286","https://openalex.org/W6637967152","https://openalex.org/W6638018090","https://openalex.org/W6684921986","https://openalex.org/W6691861496","https://openalex.org/W6692846177","https://openalex.org/W6702989015","https://openalex.org/W6728925229","https://openalex.org/W6731842068","https://openalex.org/W6734517396","https://openalex.org/W6741002519","https://openalex.org/W6742461812","https://openalex.org/W6752133560","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W8302103","https://openalex.org/W3171631314","https://openalex.org/W2674584172","https://openalex.org/W2967743314","https://openalex.org/W2606825221","https://openalex.org/W2184085865","https://openalex.org/W2064245428","https://openalex.org/W2170721890","https://openalex.org/W2122871747","https://openalex.org/W3114279067"],"abstract_inverted_index":{"Achieving":[0],"effective":[1],"task":[2],"performance":[3,223],"on":[4,72,180,204,224],"real":[5,64,114,181,225],"mobile":[6,76],"robots":[7,65,226],"is":[8,129],"a":[9,67,73,106,130,136,140,164],"great":[10],"challenge":[11,41],"when":[12],"hand-coding":[13],"algorithms,":[14],"both":[15],"due":[16],"to":[17,37,111,134],"the":[18,35,55,58,80,144,152,175,187,197,211,230],"amount":[19],"of":[20,47,57,60,75,166,199],"effort":[21],"involved":[22],"and":[23,88,124,146,154,161,169],"manually":[24],"tuned":[25],"parameters":[26,49],"required":[27],"for":[28,50,126,206],"each":[29],"skill.":[30],"Learning":[31,109],"algorithms":[32],"instead":[33],"have":[34,221],"potential":[36],"lighten":[38],"up":[39],"this":[40,99],"by":[42,227],"using":[43,105,163],"one":[44],"single":[45],"set":[46],"training":[48,160],"learning":[51,62],"different":[52],"skills,":[53],"but":[54],"question":[56],"feasibility":[59],"such":[61],"in":[63,85,118,219],"remains":[66],"research":[68],"pursuit.":[69],"We":[70,142,157],"focus":[71],"kind":[74],"robot":[77,81,95,115],"system":[78],"-":[79],"soccer":[82],"\u201csmall-size\u201d":[83],"domain,":[84],"which":[86,127],"tactical":[87],"high-level":[89],"team":[90],"strategies":[91],"build":[92],"upon":[93],"individual":[94],"ball-based":[96],"skills.":[97,209],"In":[98,210],"paper,":[100],"we":[101,173,213],"present":[102],"our":[103,159,216],"work":[104],"Deep":[107],"Reinforcement":[108],"algorithm":[110],"learn":[112],"three":[113,208],"primitive":[116],"skills":[117,189],"continuous":[119],"action":[120,147],"space:":[121],"go-to-ball,":[122],"turn-and-shoot":[123],"shoot-goalie,":[125],"there":[128],"clear":[131],"success":[132,194],"metric":[133],"reach":[135],"destination":[137],"or":[138],"score":[139],"goal.":[141],"introduce":[143],"state":[145],"representation,":[148],"as":[149,151],"well":[150],"reward":[153],"network":[155],"architecture.":[156],"describe":[158],"testing":[162],"simulator":[165],"high":[167],"physical":[168],"hardware":[170],"fidelity.":[171],"Then":[172],"test":[174],"policies":[176,217],"trained":[177,218],"from":[178],"simulation":[179,220],"robots.":[182],"Our":[183],"results":[184],"show":[185,214],"that":[186,215],"learned":[188],"achieve":[190],"an":[191],"overall":[192],"better":[193],"rate":[195],"at":[196],"expense":[198],"taking":[200],"0.29":[201],"seconds":[202],"slower":[203],"average":[205],"all":[207],"end,":[212],"good":[222],"directly":[228],"transferring":[229],"policy.":[231]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}