A Large Area Robotic Skin with Sparsely Embedded Microphones for Human-Robot Tactile Communication

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dc.contributor.authorYang, Min Jinko
dc.contributor.authorPark, Kyungseoko
dc.contributor.authorKim, Jungko
dc.date.accessioned2023-09-07T02:02:08Z-
dc.date.available2023-09-07T02:02:08Z-
dc.date.created2023-09-07-
dc.date.issued2021-05-30-
dc.identifier.citation2021 IEEE International Conference on Robotics and Automation (ICRA), pp.3248 - 3254-
dc.identifier.issn1050-4729-
dc.identifier.urihttp://hdl.handle.net/10203/312295-
dc.description.abstractA human can socially interact in a non-verbal manner by understanding the intention behind a tactile stimulus. Patting on one's back is one of tactile communications, which is considered as a sign of encouragement in most cultures. The majority of such tactile communication is carried out by a dynamic tactile on large passive body parts and differently interpreted by how and where on the body is touched. Thus any robotic system that physically interacts with a human requires a dynamic tactile sensor for further social interaction. This paper presents a large dynamic tactile sensor that could cover a robot's passive body parts using a few sparsely distributed microphones to cover a large area in an efficient manner. A porous structured mesh, neoprene, and loop fabric are used to form a sensor's skin that could well generate and transfer a signal to distributed microphones when a touch is introduced. TDOA source localisation algorithms are implemented to find the touch point locating in between the distributed microphones, and a simple convolutional neural network is trained to classify a type of the touch. A localising performance is qualitatively achieved in a testbed of the sensor and applied to a mannequin's back to show the applicability, which classified a touch into six classes with an accuracy of 88 %.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleA Large Area Robotic Skin with Sparsely Embedded Microphones for Human-Robot Tactile Communication-
dc.typeConference-
dc.identifier.wosid000765738802093-
dc.identifier.scopusid2-s2.0-85125476182-
dc.type.rimsCONF-
dc.citation.beginningpage3248-
dc.citation.endingpage3254-
dc.citation.publicationname2021 IEEE International Conference on Robotics and Automation (ICRA)-
dc.identifier.conferencecountryCC-
dc.identifier.conferencelocationXi'an-
dc.identifier.doi10.1109/icra48506.2021.9561898-
dc.contributor.localauthorKim, Jung-
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ME-Conference Papers(학술회의논문)
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