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dc.contributor.authorKim, Gyuwon-
dc.contributor.authorHwang, Donghyun-
dc.date.accessioned2024-01-19T08:33:06Z-
dc.date.available2024-01-19T08:33:06Z-
dc.date.created2023-11-17-
dc.date.issued2023-09-
dc.identifier.issn1530-437X-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/113257-
dc.description.abstractThis article introduces an approach to utilize a barometric pressure sensor chip (BPSC) as a slip-detecting tactile sensor alongside normal force estimation. This barometer-based sensor has many advantages, such as inexpensiveness, high sensitivity, simplicity to fabricate, and ease to customize, and has been utilized to measure normal directional force. Meanwhile, analyzing frequency due to vibration during slip can expand sensor performance to detect slip for stable and accurate grasping in robotic applications. This study aims to explore slip detectability with parametric analysis and assess its effectiveness with unknown daily objects. First, the slip is detected by observing signal fluctuations by adopting discrete wavelet transform (DWT) to analyze the frequency in real time. Next, the parameters affecting the slip detectability (i.e., slip velocity, preloaded force, cast soft material thickness, and object surface roughness) are investigated. Here, a signal-to-noise ratio (SNR) is calculated for further analysis. After that, the decoupling ability of slip from nonslip (e.g., normal force) is assessed by setting a threshold, and the slip detectability is further assessed under the gravitational effect. Moreover, slip direction detectability is explored with arrayed BPSCs following the identical slip detection method using DWT and threshold. Finally, the practical effectiveness of the proposed sensor is shown with a commercial robotic gripper, which reacts to strengthen grasp force when the slip is detected with unknown objects.-
dc.languageEnglish-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.titleExperimental Characterization on Slip Detectability of Barometer-Based Tactile Sensor-
dc.typeArticle-
dc.identifier.doi10.1109/JSEN.2023.3297170-
dc.description.journalClass1-
dc.identifier.bibliographicCitationIEEE Sensors Journal, v.23, no.18, pp.21803 - 21811-
dc.citation.titleIEEE Sensors Journal-
dc.citation.volume23-
dc.citation.number18-
dc.citation.startPage21803-
dc.citation.endPage21811-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid001090399700135-
dc.identifier.scopusid2-s2.0-85166773364-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalResearchAreaPhysics-
dc.type.docTypeArticle-
dc.subject.keywordPlusROBOTICS-
dc.subject.keywordAuthorBarometer-based tactile sensor-
dc.subject.keywordAuthordiscrete wavelet transform (DWT)-
dc.subject.keywordAuthorslip detection-
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KIST Article > 2023
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