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Improving Human Safety Through Motion Planning, Machine Learning, and an Assistive Exoskeleton
Improving Human Safety Through Motion Planning, Machine Learning, and an Assistive Exoskeleton
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105511
- ISBN
- 9798263329679
- DDC
- 660
- 저자명
- Bajpai, Aakash.
- 서명/저자
- Improving Human Safety Through Motion Planning, Machine Learning, and an Assistive Exoskeleton
- 발행사항
- [Sl] : Georgia Institute of Technology, 2023
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2023
- 형태사항
- 153 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
- 주기사항
- Advisor: Mazumdar, Anirban;Young, Aarong.
- 학위논문주기
- Thesis (Ph.D.)--Georgia Institute of Technology, 2023.
- 초록/해제
- 요약This work aims to address fundamental questions and create solutions to improve human abilityand safety in dangerous unstructured environments. People are inherently cognitively and phys-ically limited. Moreover, we are often perceptually saturated, limiting our ability to respond todynamic obstacles such as falling debris, runaway vehicles, or intelligent adversaries. This the-sis research addresses these mental and physical limitations through three aims. In Aim 1, weinvestigate how to effectively communicate with people with various perceptual cues to enablemore effective evasion behaviors. We then present, optimize, and validate a human-centric motionplanner which further improves human ability. In Aim 2, we design machine-learning-based in-tention recognition algorithms to identify discrete directional motions on offline data and identifylower dimensional motion primitives for real-time control. In Aim 3, we design, characterize, andvalidate a quasi-direct drive hip exoskeleton on several activities ranging from cyclic to dynamictasks. Long term, these aims could be integrated into an environmentally aware system of mobilerobots monitoring the environment and feeding information to a situation awareness enhancingactive exoskeleton that can assist in daily tasks while also protecting operators from workplace towar zone.
- 일반주제명
- Aluminum
- 일반주제명
- Design
- 일반주제명
- Virtual reality
- 일반주제명
- Information technology
- 기본자료저록
- Dissertations Abstracts International. 87-05B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798263329679
■035 ▼a(MiAaPQ)AAI32308301
■035 ▼a(MiAaPQ)GeorgiaTech75547
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a660
■1001 ▼aBajpai, Aakash.
■24510▼aImproving Human Safety Through Motion Planning, Machine Learning, and an Assistive Exoskeleton
■260 ▼a[Sl]▼bGeorgia Institute of Technology▼c2023
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2023
■300 ▼a153 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: B.
■500 ▼aAdvisor: Mazumdar, Anirban;Young, Aarong.
■5021 ▼aThesis (Ph.D.)--Georgia Institute of Technology, 2023.
■520 ▼aThis work aims to address fundamental questions and create solutions to improve human abilityand safety in dangerous unstructured environments. People are inherently cognitively and phys-ically limited. Moreover, we are often perceptually saturated, limiting our ability to respond todynamic obstacles such as falling debris, runaway vehicles, or intelligent adversaries. This the-sis research addresses these mental and physical limitations through three aims. In Aim 1, weinvestigate how to effectively communicate with people with various perceptual cues to enablemore effective evasion behaviors. We then present, optimize, and validate a human-centric motionplanner which further improves human ability. In Aim 2, we design machine-learning-based in-tention recognition algorithms to identify discrete directional motions on offline data and identifylower dimensional motion primitives for real-time control. In Aim 3, we design, characterize, andvalidate a quasi-direct drive hip exoskeleton on several activities ranging from cyclic to dynamictasks. Long term, these aims could be integrated into an environmentally aware system of mobilerobots monitoring the environment and feeding information to a situation awareness enhancingactive exoskeleton that can assist in daily tasks while also protecting operators from workplace towar zone.
■590 ▼aSchool code: 0078.
■650 4▼aAluminum
■650 4▼aDesign
■650 4▼aVirtual reality
■650 4▼aInformation technology
■690 ▼a0389
■690 ▼a0489
■71020▼aGeorgia Institute of Technology.
■7730 ▼tDissertations Abstracts International▼g87-05B.
■790 ▼a0078
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360347▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
