{"id":"https://openalex.org/W7124910956","doi":"https://doi.org/10.1109/lra.2026.3655298","title":"A Neuromorphic Incipient Slip Detection System Using Papillae Morphology","display_name":"A Neuromorphic Incipient Slip Detection System Using Papillae Morphology","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7124910956","doi":"https://doi.org/10.1109/lra.2026.3655298"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2026.3655298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2026.3655298","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-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/A5048799482","display_name":"Yanhui Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yanhui Lu","raw_affiliation_strings":["School of Engineering Mathematics and Technology, University of Bristol, Bristol, U.K"],"raw_orcid":"https://orcid.org/0009-0009-1354-0122","affiliations":[{"raw_affiliation_string":"School of Engineering Mathematics and Technology, University of Bristol, Bristol, U.K","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zeyu Deng","orcid":"https://orcid.org/0009-0007-0033-478X"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zeyu Deng","raw_affiliation_strings":["James Watt School of Engineering, University of Glasgow, Glasgow, U.K"],"raw_orcid":"https://orcid.org/0009-0007-0033-478X","affiliations":[{"raw_affiliation_string":"James Watt School of Engineering, University of Glasgow, Glasgow, U.K","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013317847","display_name":"Stephen J. Redmond","orcid":"https://orcid.org/0000-0002-2630-5449"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Stephen J. Redmond","raw_affiliation_strings":["School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-2630-5449","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013732957","display_name":"Efi Psomopoulou","orcid":"https://orcid.org/0000-0003-3883-4097"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Efi Psomopoulou","raw_affiliation_strings":["School of Engineering Mathematics and Technology, University of Bristol, Bristol, U.K"],"raw_orcid":"https://orcid.org/0000-0003-3883-4097","affiliations":[{"raw_affiliation_string":"School of Engineering Mathematics and Technology, University of Bristol, Bristol, U.K","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123386203","display_name":"Benjamin Ward-Cherrier","orcid":null},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Benjamin Ward-Cherrier","raw_affiliation_strings":["School of Engineering Mathematics and Technology, University of Bristol, Bristol, U.K"],"raw_orcid":"https://orcid.org/0000-0001-9614-7004","affiliations":[{"raw_affiliation_string":"School of Engineering Mathematics and Technology, University of Bristol, Bristol, U.K","institution_ids":["https://openalex.org/I36234482"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07007398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"3","first_page":"2802","last_page":"2809"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.9117000102996826,"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.9117000102996826,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.02889999933540821,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10914","display_name":"Tactile and Sensory Interactions","score":0.007199999876320362,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/slip","display_name":"Slip (aerodynamics)","score":0.8432999849319458},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.7368000149726868},{"id":"https://openalex.org/keywords/slippage","display_name":"Slippage","score":0.6521999835968018},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5695000290870667},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5692999958992004},{"id":"https://openalex.org/keywords/tactile-sensor","display_name":"Tactile sensor","score":0.46480000019073486}],"concepts":[{"id":"https://openalex.org/C195268267","wikidata":"https://www.wikidata.org/wiki/Q1928883","display_name":"Slip (aerodynamics)","level":2,"score":0.8432999849319458},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.7368000149726868},{"id":"https://openalex.org/C2776096238","wikidata":"https://www.wikidata.org/wiki/Q6130172","display_name":"Slippage","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5861999988555908},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5695000290870667},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5557000041007996},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4771000146865845},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.46480000019073486},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3068999946117401},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.28200000524520874},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.28119999170303345},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27950000762939453},{"id":"https://openalex.org/C134786449","wikidata":"https://www.wikidata.org/wiki/Q3391255","display_name":"Planar","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.25440001487731934},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2515000104904175}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lra.2026.3655298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2026.3655298","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:research-information.bris.ac.uk:publications/722c0c25-86fb-485f-9856-e141918dca5e","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/722c0c25-86fb-485f-9856-e141918dca5e","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lu, Y, Deng, Z, Redmond, S J, Psomopoulou, E & Ward-Cherrier, B 2026, 'A Neuromorphic Incipient Slip Detection System Using Papillae Morphology', IEEE Robotics and Automation Letters, vol. 11, no. 3, pp. 2802-2809. https://doi.org/10.1109/LRA.2026.3655298","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.40231654047966003,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1503718778","display_name":null,"funder_award_id":"RF02021071","funder_id":"https://openalex.org/F4320320005","funder_display_name":"Royal Academy of Engineering"}],"funders":[{"id":"https://openalex.org/F4320320005","display_name":"Royal Academy of Engineering","ror":"https://ror.org/0526snb40"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1548071717","https://openalex.org/W1922760316","https://openalex.org/W2006652748","https://openalex.org/W2045222441","https://openalex.org/W2118425652","https://openalex.org/W2221877149","https://openalex.org/W2464569091","https://openalex.org/W2779500696","https://openalex.org/W2785792599","https://openalex.org/W2892010946","https://openalex.org/W2984844508","https://openalex.org/W3040838455","https://openalex.org/W3083311324","https://openalex.org/W3096386095","https://openalex.org/W3131680547","https://openalex.org/W4296125832","https://openalex.org/W4309618925","https://openalex.org/W4311413922","https://openalex.org/W4389665916","https://openalex.org/W4390224394","https://openalex.org/W4390705114","https://openalex.org/W4393270373","https://openalex.org/W4399800941","https://openalex.org/W4400643993","https://openalex.org/W4403017053","https://openalex.org/W4409233638","https://openalex.org/W4410772114","https://openalex.org/W4413926233","https://openalex.org/W4416749917"],"related_works":[],"abstract_inverted_index":{"Detecting":[0],"incipient":[1,49,79,124],"slip":[2,50,85,109,125,131],"enables":[3],"early":[4],"intervention":[5],"to":[6],"prevent":[7],"object":[8],"slippage":[9],"and":[10,29,35,62,81,144],"enhance":[11],"robotic":[12],"manipulation":[13],"safety.":[14],"Achieving":[15],"this":[16],"requires":[17],"tactile":[18,30,45],"interfaces":[19],"with":[20],"compliant,":[21],"high-sensitivity":[22],"skins":[23],"that":[24,33],"amplify":[25],"local":[26],"deformation":[27],"differences":[28],"sensing":[31,46],"pipelines":[32],"preserve":[34],"exploit":[36],"high-resolution":[37],"spatio-temporal":[38],"signals.":[39],"This":[40],"work":[41],"presents":[42],"an":[43,58],"event-based":[44],"system":[47,122,143],"for":[48,148],"detection,":[51],"built":[52],"on":[53],"the":[54,116,121,138,141],"NeuroTac":[55],"sensor,":[56],"featuring":[57],"extruding":[59],"papillae-based":[60],"skin":[61],"a":[63,101],"spiking":[64],"convolutional":[65],"neural":[66],"network":[67],"(SCNN).":[68],"The":[69],"SCNN":[70],"achieves":[71],"94.33%":[72],"accuracy":[73,94],"in":[74],"three-class":[75],"classification":[76],"(no":[77],"slip,":[78,80],"gross":[82,130],"slip)":[83],"during":[84],"conditions":[86],"induced":[87],"by":[88],"sensor":[89],"motion,":[90],"delivering":[91],"slightly":[92],"higher":[93],"than":[95],"its":[96,146],"ANN":[97],"counterparts":[98],"while":[99],"maintaining":[100],"low":[102],"theoretical":[103],"computational":[104],"cost.":[105],"Under":[106],"dynamic":[107],"gravity-induced":[108],"validation":[110],"settings,":[111],"after":[112],"temporal":[113],"smoothing":[114],"of":[115,140],"SCNN's":[117],"final-layer":[118],"spike":[119],"counts,":[120],"detects":[123],"360\u20131840":[126],"ms":[127],"before":[128],"actual":[129],"across":[132],"all":[133],"trials.":[134],"These":[135],"results":[136],"demonstrate":[137],"effectiveness":[139],"proposed":[142],"highlight":[145],"potential":[147],"future":[149],"neuromorphic":[150],"hardware":[151],"deployment.":[152]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-21T00:00:00"}