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Compressed Sensing for Scalable Robotic Tactile Skins

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서명/저자사항Compressed Sensing for Scalable Robotic Tactile Skins.
개인저자Hollis, Brayden.
단체저자명Rensselaer Polytechnic Institute. Computer Science.
발행사항[S.l.]: Rensselaer Polytechnic Institute., 2018.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2018.
형태사항125 p.
기본자료 저록Dissertation Abstracts International 79-12B(E).
Dissertation Abstract International
ISBN9780438206588
학위논문주기Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018.
일반주기 Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Stacy Patterson.
요약Tactile skins can enhance a robot's capabilities in many application domains, including whole-body manipulation, human-robot communication, and safe interaction. To support these enhancements, the expectation is that tactile skins will generate
요약First, we introduce the open-source tactile skin simulator BubbleTouch for generating tactile data since current tactile skin systems are not widely available to produce data for research. BubbleTouch uses kinematic and quasistatic mechanics to
요약We then disclose a new tactile data acquisition system for normal force tactile sensors based on compressed sensing. Compressed sensing simultaneously performs data sampling and compression. Given that the signals are sparse in some dictionary,
요약We note that we found there was no single dictionary that provided the sparsest representation for every signal, and thus, we describe a process that takes the compressed signal and decides which dictionary to use during reconstruction. The meth
요약The volume of tactile data also makes it challenging for the processing system to analyze and utilize the tactile data for various applications. We discuss the particular processing application of tactile object classification and present an app
일반주제명Computer science.
Robotics.
언어영어
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