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Leveraging Virtual Reality to Identify Personalized Control Schemes for Teleoperating Non-Anthropomorphic Robots
Leveraging Virtual Reality to Identify Personalized Control Schemes for Teleoperating Non-Anthropomorphic Robots
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105515
- ISBN
- 9798263337797
- DDC
- 620
- 서명/저자
- Leveraging Virtual Reality to Identify Personalized Control Schemes for Teleoperating Non-Anthropomorphic Robots
- 발행사항
- [Sl] : Georgia Institute of Technology, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 131 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: A.
- 주기사항
- Advisor: Chernova, Sonia.
- 학위논문주기
- Thesis (Ph.D.)--Georgia Institute of Technology, 2024.
- 초록/해제
- 요약Virtual reality (VR) has emerged as a popular teleoperation interface for robotic systems due to the immersive nature of VR interactions. In VR, users use their hands (or hand-held controllers) to interact with the environment. However, just as living animals have evolved specialized embodiments that differ from those of a human (e.g. tentacles, wings, prehensile tails, etc.), specialized robotic systems are often designed with non-anthropomorphic embodiments (e.g. treads, wheels, arms with differing degrees of freedom, etc.). Such differences in embodiment between human hands and the robot introduce challenges for the design of intuitive user teleoperation interfaces.This dissertation focuses on designing control schemes for teleoperating non-anthropomorphic robots and specifically investigates the hypothesis that users' demonstrated preferences can provide a basis for functional, personalized control schemes. Specifically, my work contributes:• A comprehensive survey of control scheme designs for teleoperating both real and virtual non-anthropomorphic robots, to characterize common design principles and identify unexplored research areas.• A VR "puppet-master" platform for identifying and validating user-generated mappings between a user's hand and a simulated robot.• An overview of users' default control scheme preferences and rationales for an example anthropomorphic and non-anthropomorphic robot arm, revealing features of a control scheme that are likely to benefit from personalization.• An analysis of model prediction error for control schemes trained on single or multiple participants and gestures, highlighting cases for which group-wise personalization is feasible and cases for which more data or more sophisticated processing methods are necessary.
- 일반주제명
- Robots
- 일반주제명
- Clustering
- 일반주제명
- Anthropomorphism
- 일반주제명
- Prostheses
- 일반주제명
- Virtual reality
- 일반주제명
- Robotics
- 일반주제명
- Cultural anthropology
- 일반주제명
- Information technology
- 기본자료저록
- Dissertations Abstracts International. 87-05A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798263337797
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■035 ▼a(MiAaPQ)GeorgiaTech75227
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a620
■1001 ▼aMolnar, Jennifer.
■24510▼aLeveraging Virtual Reality to Identify Personalized Control Schemes for Teleoperating Non-Anthropomorphic Robots
■260 ▼a[Sl]▼bGeorgia Institute of Technology▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a131 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: A.
■500 ▼aAdvisor: Chernova, Sonia.
■5021 ▼aThesis (Ph.D.)--Georgia Institute of Technology, 2024.
■520 ▼aVirtual reality (VR) has emerged as a popular teleoperation interface for robotic systems due to the immersive nature of VR interactions. In VR, users use their hands (or hand-held controllers) to interact with the environment. However, just as living animals have evolved specialized embodiments that differ from those of a human (e.g. tentacles, wings, prehensile tails, etc.), specialized robotic systems are often designed with non-anthropomorphic embodiments (e.g. treads, wheels, arms with differing degrees of freedom, etc.). Such differences in embodiment between human hands and the robot introduce challenges for the design of intuitive user teleoperation interfaces.This dissertation focuses on designing control schemes for teleoperating non-anthropomorphic robots and specifically investigates the hypothesis that users' demonstrated preferences can provide a basis for functional, personalized control schemes. Specifically, my work contributes:• A comprehensive survey of control scheme designs for teleoperating both real and virtual non-anthropomorphic robots, to characterize common design principles and identify unexplored research areas.• A VR "puppet-master" platform for identifying and validating user-generated mappings between a user's hand and a simulated robot.• An overview of users' default control scheme preferences and rationales for an example anthropomorphic and non-anthropomorphic robot arm, revealing features of a control scheme that are likely to benefit from personalization.• An analysis of model prediction error for control schemes trained on single or multiple participants and gestures, highlighting cases for which group-wise personalization is feasible and cases for which more data or more sophisticated processing methods are necessary.
■590 ▼aSchool code: 0078.
■650 4▼aRobots
■650 4▼aClustering
■650 4▼aAnthropomorphism
■650 4▼aProstheses
■650 4▼aVirtual reality
■650 4▼aRobotics
■650 4▼aCultural anthropology
■650 4▼aInformation technology
■690 ▼a0771
■690 ▼a0326
■690 ▼a0489
■71020▼aGeorgia Institute of Technology.
■7730 ▼tDissertations Abstracts International▼g87-05A.
■790 ▼a0078
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360376▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
