{"id":"https://openalex.org/W7131075473","doi":"https://doi.org/10.1109/robio66223.2025.11379817","title":"Passive outperforms active whisking in a deep learning shape classification task","display_name":"Passive outperforms active whisking in a deep learning shape classification task","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W7131075473","doi":"https://doi.org/10.1109/robio66223.2025.11379817"},"language":null,"primary_location":{"id":"doi:10.1109/robio66223.2025.11379817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio66223.2025.11379817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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/A5039845088","display_name":"Soumo Emmanuel Arnaud","orcid":null},"institutions":[{"id":"https://openalex.org/I51532219","display_name":"University of Lincoln","ror":"https://ror.org/03yeq9x20","country_code":"GB","type":"education","lineage":["https://openalex.org/I51532219"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Soumo Emmanuel Arnaud","raw_affiliation_strings":["School of Computer Science, University of Lincoln,Lincoln,UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Lincoln,Lincoln,UK","institution_ids":["https://openalex.org/I51532219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084443795","display_name":"Dimitris Paparas","orcid":null},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dimitris Paparas","raw_affiliation_strings":["University of Cambridge,Cambridge,UK"],"affiliations":[{"raw_affiliation_string":"University of Cambridge,Cambridge,UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Robert L. Stevenson","orcid":null},"institutions":[{"id":"https://openalex.org/I51532219","display_name":"University of Lincoln","ror":"https://ror.org/03yeq9x20","country_code":"GB","type":"education","lineage":["https://openalex.org/I51532219"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Robert L. Stevenson","raw_affiliation_strings":["School of Computer Science, University of Lincoln,Lincoln,UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Lincoln,Lincoln,UK","institution_ids":["https://openalex.org/I51532219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101892404","display_name":"Charles Fox","orcid":"https://orcid.org/0000-0002-6695-8081"},"institutions":[{"id":"https://openalex.org/I51532219","display_name":"University of Lincoln","ror":"https://ror.org/03yeq9x20","country_code":"GB","type":"education","lineage":["https://openalex.org/I51532219"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Charles Fox","raw_affiliation_strings":["School of Computer Science, University of Lincoln,Lincoln,UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Lincoln,Lincoln,UK","institution_ids":["https://openalex.org/I51532219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039845088"],"corresponding_institution_ids":["https://openalex.org/I51532219"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68831974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"344","last_page":"350"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.0763000026345253,"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"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.0763000026345253,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.07169999927282333,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.058800000697374344,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/whisking-in-animals","display_name":"Whisking in animals","score":0.9830999970436096},{"id":"https://openalex.org/keywords/whisker","display_name":"Whisker","score":0.6575000286102295},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44859999418258667},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4068000018596649},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.40070000290870667},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4000999927520752}],"concepts":[{"id":"https://openalex.org/C145065098","wikidata":"https://www.wikidata.org/wiki/Q913572","display_name":"Whisking in animals","level":3,"score":0.9830999970436096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6643000245094299},{"id":"https://openalex.org/C179111330","wikidata":"https://www.wikidata.org/wiki/Q901525","display_name":"Whisker","level":2,"score":0.6575000286102295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6572999954223633},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45649999380111694},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.40070000290870667},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C116134602","wikidata":"https://www.wikidata.org/wiki/Q913572","display_name":"Whiskers","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3546999990940094},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30570000410079956},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3001999855041504},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2754000127315521}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/robio66223.2025.11379817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio66223.2025.11379817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5318487882614136}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1583231601","https://openalex.org/W1968855001","https://openalex.org/W1980115401","https://openalex.org/W2001383746","https://openalex.org/W2008179589","https://openalex.org/W2074954464","https://openalex.org/W2077270141","https://openalex.org/W2077777602","https://openalex.org/W2097923922","https://openalex.org/W2098523040","https://openalex.org/W2101511752","https://openalex.org/W2102236613","https://openalex.org/W2127608938","https://openalex.org/W2128204410","https://openalex.org/W2131704066","https://openalex.org/W2143825860","https://openalex.org/W2145149052","https://openalex.org/W2148948992","https://openalex.org/W2165421944","https://openalex.org/W2416119024","https://openalex.org/W2419118448","https://openalex.org/W2484779873","https://openalex.org/W2519827695","https://openalex.org/W2593615053","https://openalex.org/W2620913710","https://openalex.org/W2624516165","https://openalex.org/W2760171912","https://openalex.org/W2804671087","https://openalex.org/W2806458000","https://openalex.org/W2807275354","https://openalex.org/W3003964794","https://openalex.org/W4388205018","https://openalex.org/W4400770620","https://openalex.org/W4405873115","https://openalex.org/W4405873340"],"related_works":[],"abstract_inverted_index":{"Tactile":[0],"sensing":[1,89,177],"with":[2,111],"robotic":[3],"whiskers":[4,22],"has":[5,57],"been":[6,59],"shown":[7],"to":[8,35,38,126,136,149,170],"enable":[9,171],"shape":[10,91,123],"and":[11,16,158],"texture":[12],"recognition.":[13],"Biological":[14],"studies":[15],"robot":[17],"practicalities":[18],"-":[19,23],"avoiding":[20],"breaking":[21],"strongly":[24],"suggest":[25],"active":[26,47,85,106,129],"whisking":[27,42,48,104,119],"(i.e.":[28,40],"retracting":[29],"the":[30,53,117,147],"whisker":[31,51,88,142,176],"shortly":[32],"after":[33],"contact)":[34],"be":[36,150,164],"preferable":[37],"passive":[39,87,103,118],"open-loop":[41],"patterns":[43],"during":[44],"contact).":[45],"While":[46],"may":[49,76],"protect":[50],"sensors,":[52],"effect":[54],"on":[55,116],"accuracy":[56,139],"not":[58],"studied":[60],"in":[61,180],"detail,":[62],"though":[63],"there":[64],"are":[65,146],"some":[66],"early":[67],"indications":[68],"using":[69,93,152],"suboptimal,":[70],"pre-deep":[71],"learning":[72,97],"classifiers":[73],"that":[74,102],"it":[75],"degrade":[77],"accuracy.":[78],"We":[79],"perform":[80],"a":[81,153,167],"controlled":[82],"study":[83],"of":[84,114],"vs":[86],"for":[90,128,140],"recognition,":[92],"multiple":[94],"current":[95],"deep":[96],"models.":[98],"Experimental":[99],"results":[100],"show":[101],"outperforms":[105],"classification":[107],"performance":[108],"by":[109],"10%,":[110],"an":[112],"Fl-score":[113],"0.85":[115],"dataset":[120],"across":[121],"various":[122],"categories,":[124],"compared":[125],"0.74":[127],"whisking.":[130],"This":[131],"raises":[132],"questions":[133],"about":[134],"how":[135],"trade":[137],"off":[138],"physical":[141],"protection.":[143],"Our":[144],"experiments":[145],"first":[148],"performed":[151],"completely":[154],"open":[155],"source":[156],"hardware":[157],"software":[159],"stack,":[160],"so":[161],"they":[162],"can":[163],"used":[165],"as":[166,179,184],"replicable":[168],"baseline":[169],"future":[172],"metric-driven":[173],"incremental":[174],"improvement":[175],"research,":[178],"mature":[181],"fields":[182],"such":[183],"machine":[185],"vision.":[186]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-02-24T00:00:00"}
