{"id":"https://openalex.org/W3132836720","doi":"https://doi.org/10.1109/iros45743.2020.9341016","title":"Using Machine Learning for Material Detection with Capacitive Proximity Sensors","display_name":"Using Machine Learning for Material Detection with Capacitive Proximity Sensors","publication_year":2020,"publication_date":"2020-10-24","ids":{"openalex":"https://openalex.org/W3132836720","doi":"https://doi.org/10.1109/iros45743.2020.9341016","mag":"3132836720"},"language":"en","primary_location":{"id":"doi:10.1109/iros45743.2020.9341016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5067207198","display_name":"Yitao Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I2610724","display_name":"Chemnitz University of Technology","ror":"https://ror.org/00a208s56","country_code":"DE","type":"education","lineage":["https://openalex.org/I2610724"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Yitao Ding","raw_affiliation_strings":["Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany"],"affiliations":[{"raw_affiliation_string":"Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany","institution_ids":["https://openalex.org/I2610724"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009478024","display_name":"Hannes Kisner","orcid":null},"institutions":[{"id":"https://openalex.org/I2610724","display_name":"Chemnitz University of Technology","ror":"https://ror.org/00a208s56","country_code":"DE","type":"education","lineage":["https://openalex.org/I2610724"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hannes Kisner","raw_affiliation_strings":["Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany"],"affiliations":[{"raw_affiliation_string":"Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany","institution_ids":["https://openalex.org/I2610724"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077768493","display_name":"Tianlin Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I2610724","display_name":"Chemnitz University of Technology","ror":"https://ror.org/00a208s56","country_code":"DE","type":"education","lineage":["https://openalex.org/I2610724"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tianlin Kong","raw_affiliation_strings":["Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany"],"affiliations":[{"raw_affiliation_string":"Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany","institution_ids":["https://openalex.org/I2610724"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102866538","display_name":"Ulrike Thomas","orcid":"https://orcid.org/0000-0003-3211-4208"},"institutions":[{"id":"https://openalex.org/I2610724","display_name":"Chemnitz University of Technology","ror":"https://ror.org/00a208s56","country_code":"DE","type":"education","lineage":["https://openalex.org/I2610724"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ulrike Thomas","raw_affiliation_strings":["Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany"],"affiliations":[{"raw_affiliation_string":"Lab of Robotics and Human-Machine Interaction, Chemnitz University of Technology, Chemnitz, Germany","institution_ids":["https://openalex.org/I2610724"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067207198"],"corresponding_institution_ids":["https://openalex.org/I2610724"],"apc_list":null,"apc_paid":null,"fwci":1.186,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.79488759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"10424","last_page":"10429"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9933000206947327,"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":0.9933000206947327,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/capacitive-sensing","display_name":"Capacitive sensing","score":0.7938926219940186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6472973823547363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6415929794311523},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5919667482376099},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5919199585914612},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5853419303894043},{"id":"https://openalex.org/keywords/electrical-impedance","display_name":"Electrical impedance","score":0.5199112296104431},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4951285421848297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4571090340614319},{"id":"https://openalex.org/keywords/proximity-sensor","display_name":"Proximity sensor","score":0.4471761882305145},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4407731890678406},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3804408311843872},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19739791750907898},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.10721412301063538}],"concepts":[{"id":"https://openalex.org/C206755178","wikidata":"https://www.wikidata.org/wiki/Q1131271","display_name":"Capacitive sensing","level":2,"score":0.7938926219940186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6472973823547363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6415929794311523},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5919667482376099},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5919199585914612},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5853419303894043},{"id":"https://openalex.org/C17829176","wikidata":"https://www.wikidata.org/wiki/Q179043","display_name":"Electrical impedance","level":2,"score":0.5199112296104431},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4951285421848297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4571090340614319},{"id":"https://openalex.org/C135403697","wikidata":"https://www.wikidata.org/wiki/Q796765","display_name":"Proximity sensor","level":2,"score":0.4471761882305145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4407731890678406},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3804408311843872},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19739791750907898},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.10721412301063538},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros45743.2020.9341016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1974436840","https://openalex.org/W2021979931","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2291961022","https://openalex.org/W2332077312","https://openalex.org/W2773348725","https://openalex.org/W2774082069","https://openalex.org/W2791288858","https://openalex.org/W2802840089","https://openalex.org/W2909986727","https://openalex.org/W2910499561","https://openalex.org/W2940682483","https://openalex.org/W2947409955","https://openalex.org/W2951453290","https://openalex.org/W2963304300","https://openalex.org/W2994492048","https://openalex.org/W3016311333","https://openalex.org/W6631190155","https://openalex.org/W6686164453","https://openalex.org/W6745081244","https://openalex.org/W6747002101","https://openalex.org/W6751497200"],"related_works":["https://openalex.org/W340201814","https://openalex.org/W2152098532","https://openalex.org/W4386571252","https://openalex.org/W2045180228","https://openalex.org/W2731973168","https://openalex.org/W241455228","https://openalex.org/W2155218958","https://openalex.org/W4283740974","https://openalex.org/W3082546580","https://openalex.org/W2166944910"],"abstract_inverted_index":{"The":[0,12,56],"ability":[1],"of":[2,59],"detecting":[3],"materials":[4,61,92],"plays":[5],"an":[6,30],"important":[7],"role":[8],"in":[9,26],"robotic":[10],"applications.":[11],"robot":[13],"can":[14],"incorporate":[15],"the":[16,112,117],"information":[17,115],"from":[18,49,99,116],"contactless":[19],"material":[20,54,113],"detection":[21],"and":[22,65,70,93],"adapt":[23],"its":[24],"behavior":[25],"how":[27,33],"it":[28,34],"grasps":[29],"object":[31],"or":[32],"walks":[35],"on":[36,46,89],"specific":[37,114],"surfaces.":[38],"In":[39],"this,":[40],"paper":[41],"we":[42],"apply":[43],"machine":[44],"learning":[45],"impedance":[47,118],"spectra":[48,58],"capacitive":[50],"proximity":[51],"sensors":[52],"for":[53],"detection.":[55],"unique":[57],"certain":[60],"only":[62],"differ":[63],"slightly":[64],"are":[66,108],"subject":[67],"to":[68,80,103,110],"noise":[69],"scaling":[71],"effects":[72],"during":[73],"each":[74],"measurement.":[75],"A":[76],"best-fit":[77],"classification":[78,88,96],"approach":[79],"pre-recorded":[81],"data":[82],"is":[83],"therefore":[84],"inaccurate.":[85],"We":[86],"perform":[87],"ten":[90],"different":[91,95],"evaluate":[94],"algorithms":[97],"ranging":[98],"simple":[100],"k-NN":[101],"approaches":[102],"artificial":[104],"neural":[105],"networks,":[106],"which":[107],"able":[109],"extract":[111],"spectra.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
