{"id":"https://openalex.org/W7163362827","doi":"https://doi.org/10.48550/arxiv.2606.03545","title":"Static and Dynamic Representations for Tactile Contact-Angle Estimation with Event-Based Sensors","display_name":"Static and Dynamic Representations for Tactile Contact-Angle Estimation with Event-Based Sensors","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163362827","doi":"https://doi.org/10.48550/arxiv.2606.03545"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03545","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03545","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.03545","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137798848","display_name":"Yanhui Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Yanhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013732957","display_name":"Efi Psomopoulou","orcid":"https://orcid.org/0000-0003-3883-4097"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Psomopoulou, Efi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137735186","display_name":"Benjamin Ward-Cherrier","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ward-Cherrier, Benjamin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.3206999897956848,"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":0.3206999897956848,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.29109999537467957,"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.0917000025510788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.7182999849319458},{"id":"https://openalex.org/keywords/tactile-sensor","display_name":"Tactile sensor","score":0.5554999709129333},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.45739999413490295},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4426000118255615},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.3912000060081482},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3702000081539154},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.3407000005245209}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7182999849319458},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6409000158309937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5771999955177307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5748000144958496},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.5554999709129333},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.45739999413490295},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4426000118255615},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3912000060081482},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3702000081539154},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C150415221","wikidata":"https://www.wikidata.org/wiki/Q40687","display_name":"Robotic arm","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.29679998755455017},{"id":"https://openalex.org/C2780902562","wikidata":"https://www.wikidata.org/wiki/Q1154141","display_name":"Indentation","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C2987691683","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling time","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03545","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03545","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.03545","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03545","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Event-based":[0],"tactile":[1,22,78],"sensing":[2],"offers":[3],"low-latency":[4],"signal":[5],"acquisition":[6],"for":[7,75],"contact-rich":[8],"robotic":[9,82],"interaction.":[10],"This":[11],"paper":[12],"investigates":[13],"contact-angle":[14],"estimation":[15,80],"using":[16],"event":[17,37],"streams":[18],"from":[19],"an":[20],"event-based":[21,77],"sensor":[23,110],"(NeuroTac)":[24],"and":[25,48,95,112,132],"compares":[26],"three":[27],"event-derived":[28],"spatial":[29],"contour":[30],"representations:":[31],"a":[32,39,43,102,113],"dynamic":[33,94],"representation":[34,41,58,86],"capturing":[35],"recent":[36],"activity,":[38],"static":[40,85],"recovering":[42],"more":[44],"persistent":[45],"contact":[46],"state,":[47],"their":[49,73],"combined":[50,96],"representation.":[51],"Across":[52],"the":[53,93,137],"evaluated":[54],"motion":[55,122],"scenarios,":[56],"all":[57,68],"pipelines":[59],"exhibited":[60,126],"P99":[61],"processing":[62],"latency":[63],"below":[64],"10":[65],"ms":[66],"at":[67],"tested":[69],"sampling":[70],"intervals,":[71],"demonstrating":[72],"potential":[74],"high-frequency":[76],"angle":[79],"in":[81],"manipulation.":[83],"The":[84],"consistently":[87],"achieved":[88],"marginally":[89],"better":[90],"performance":[91,128],"than":[92,136],"representations":[97],"under":[98],"scenario-specific":[99],"training,":[100],"yielding":[101],"mean":[103,115],"overall":[104],"MAE":[105,116],"of":[106,117],"0.160\u00b0":[107],"during":[108,119],"continuous":[109],"rolling":[111],"stop-phase":[114],"0.251\u00b0":[118],"randomly":[120],"inserted":[121],"interruptions.":[123],"It":[124],"also":[125],"smaller":[127],"fluctuations":[129],"across":[130],"speed":[131],"indentation":[133],"depth":[134],"variations":[135],"other":[138],"two":[139],"representations.":[140]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-04T00:00:00"}
