{"id":"https://openalex.org/W2568901734","doi":"https://doi.org/10.1109/humanoids.2016.7803258","title":"Material recognition CNNs and hierarchical planning for biped robot locomotion on slippery terrain","display_name":"Material recognition CNNs and hierarchical planning for biped robot locomotion on slippery terrain","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2568901734","doi":"https://doi.org/10.1109/humanoids.2016.7803258","mag":"2568901734"},"language":"en","primary_location":{"id":"doi:10.1109/humanoids.2016.7803258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/humanoids.2016.7803258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1706.08685","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Martim Brandao","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Martim Brandao","raw_affiliation_strings":["Graduate School of Advanced Science and Engineering, Waseda University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Science and Engineering, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yukitoshi Minami Shiguematsu","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yukitoshi Minami Shiguematsu","raw_affiliation_strings":["Graduate School of Advanced Science and Engineering, Waseda University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Science and Engineering, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kenji Hashimoto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kenji Hashimoto","raw_affiliation_strings":["Waseda Institute for Advanced Study, Humanoid Robotics Institute (HRI)"],"affiliations":[{"raw_affiliation_string":"Waseda Institute for Advanced Study, Humanoid Robotics Institute (HRI)","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Atsuo Takanishi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsuo Takanishi","raw_affiliation_strings":["Department of Modern Mechanical Engineering, Waseda University"],"affiliations":[{"raw_affiliation_string":"Department of Modern Mechanical Engineering, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":2.6237,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.89676134,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"81","last_page":"88"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10879","display_name":"Robotic Locomotion and Control","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10879","display_name":"Robotic Locomotion and Control","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10812","display_name":"Human Pose and Action Recognition","score":0.9977999925613403,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.996399998664856,"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/robot","display_name":"Robot","score":0.6722999811172485},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5827999711036682},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.5382999777793884},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.49140000343322754},{"id":"https://openalex.org/keywords/biped-robot","display_name":"Biped robot","score":0.483599990606308},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.43619999289512634},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4350999891757965},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.3930000066757202}],"concepts":[{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6722999811172485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6097000241279602},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5827999711036682},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5382999777793884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5307000279426575},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5256999731063843},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.49140000343322754},{"id":"https://openalex.org/C3019356360","wikidata":"https://www.wikidata.org/wiki/Q372949","display_name":"Biped robot","level":3,"score":0.483599990606308},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.43619999289512634},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4350999891757965},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.3165000081062317},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.31619998812675476},{"id":"https://openalex.org/C2778835581","wikidata":"https://www.wikidata.org/wiki/Q2916098","display_name":"Autonomous robot","level":4,"score":0.29840001463890076},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.29109999537467957},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.28870001435279846},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/humanoids.2016.7803258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/humanoids.2016.7803258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1706.08685","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1706.08685","pdf_url":"https://arxiv.org/pdf/1706.08685","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1706.08685","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1706.08685","pdf_url":"https://arxiv.org/pdf/1706.08685","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1499277207","https://openalex.org/W1751898876","https://openalex.org/W1945123189","https://openalex.org/W1946140191","https://openalex.org/W1953465585","https://openalex.org/W2006010000","https://openalex.org/W2012747043","https://openalex.org/W2015149365","https://openalex.org/W2042408133","https://openalex.org/W2055302526","https://openalex.org/W2095143145","https://openalex.org/W2095801433","https://openalex.org/W2125215748","https://openalex.org/W2140110047","https://openalex.org/W2142224528","https://openalex.org/W2145477224","https://openalex.org/W2149036798","https://openalex.org/W2152864241","https://openalex.org/W2158070864","https://openalex.org/W2175812528","https://openalex.org/W2462722718","https://openalex.org/W2570886061","https://openalex.org/W6637373629","https://openalex.org/W6639780620","https://openalex.org/W6642513403","https://openalex.org/W6683620479","https://openalex.org/W6756486208","https://openalex.org/W6812115717"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1,19],"paper":[2],"we":[3],"tackle":[4],"the":[5,42,100,116,124],"problem":[6,27],"of":[7,78,90,123,164],"visually":[8],"predicting":[9],"surface":[10],"friction":[11,39,71,91,101,144,158],"for":[12,30,61,127],"environments":[13],"with":[14,37,86,93,176],"diverse":[15,35],"surfaces,":[16],"and":[17,72,107,114,135,145,152,167],"integrating":[18],"knowledge":[20],"into":[21,103],"biped":[22],"robot":[23,32,62,173],"locomotion":[24,33,63,136],"planning.":[25],"The":[26],"is":[28],"essential":[29],"autonomous":[31,133],"since":[34],"surfaces":[36,175],"varying":[38],"abound":[40],"in":[41,161],"real":[43,162,172],"world,":[44],"from":[45,75],"wood":[46],"to":[47,69],"ceramic":[48],"tiles,":[49],"grass":[50],"or":[51,57],"ice,":[52],"which":[53,140],"may":[54],"cause":[55],"difficulties":[56],"huge":[58],"energy":[59],"costs":[60,119],"if":[64],"not":[65,142],"considered.":[66],"We":[67,96,155],"propose":[68],"estimate":[70],"its":[73,146],"uncertainty":[74],"visual":[76],"estimation":[77],"material":[79],"classes":[80],"using":[81,111],"convolutional":[82],"neural":[83],"networks,":[84],"together":[85],"probability":[87],"distribution":[88],"functions":[89],"associated":[92],"each":[94],"material.":[95],"then":[97],"robustly":[98],"integrate":[99],"predictions":[102],"a":[104,171],"hierarchical":[105],"(footstep":[106],"full-body)":[108],"planning":[109,125,168],"method":[110,126],"chance":[112],"constraints,":[113],"optimize":[115],"same":[117],"trajectory":[118,153],"at":[120],"both":[121],"levels":[122],"consistency.":[128],"Our":[129],"solution":[130],"achieves":[131],"fully":[132],"perception":[134],"on":[137,170],"slippery":[138],"terrain,":[139],"considers":[141],"only":[143],"uncertainty,":[147],"but":[148],"also":[149],"collision,":[150],"stability":[151],"cost.":[154],"show":[156],"promising":[157],"prediction":[159],"results":[160],"pictures":[163],"outdoor":[165],"scenarios,":[166],"experiments":[169],"facing":[174],"different":[177],"friction.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2017-01-13T00:00:00"}