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Rendering, Replicating, and Adapting Human Motions on a Cable Robot for Artistic Painting
Rendering, Replicating, and Adapting Human Motions on a Cable Robot for Artistic Painting
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105511
- ISBN
- 9798263331252
- DDC
- 000
- 저자명
- Chen, Gerry.
- 서명/저자
- Rendering, Replicating, and Adapting Human Motions on a Cable Robot for Artistic Painting
- 발행사항
- [Sl] : Georgia Institute of Technology, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 205 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
- 주기사항
- Advisor: Dellaert, Frank;Hutchinson, Seth.
- 학위논문주기
- Thesis (Ph.D.)--Georgia Institute of Technology, 2024.
- 초록/해제
- 요약Artists have continually pushed their crafts to embody the furthest reaches of human capabilities, from delicate painting to athletic performances, highlighting the potential for robots to emulate these skills. This work aims to study the task of robot graffiti painting in three parts: rendering, replicating, and adapting human motions, ultimately contributing to the fields of robot art, cable robot control, motion planning, and generative modeling.In this work, three parts to the problem of artistic painting guided by human motions are addressed: rendering a digital artwork in paint with a cable robot; replicating human input motions as closely as possible; and adapting human input motions to accommodate for differences in level of detail, style, and artistic medium. Through the difficult, interaction-rich task of robot art, modern challenges in human-robot collaboration can be studied. In particular, techniques for robot motion control through natural input interfaces drawn from human motions are developed. Rendering paint requires advances in state estimation and control techniques for fast, fluid motions on a cable robot. Replicating human motions bridges the input motions and robot kino-dynamic capabilities, requiring advances in optima ltrajectory retiming techniques. Finally, adapting goes beyond rote replication by augmenting input motions to better fit the composition, style, and medium intended by the robot-artistteam, requiring embodiment-specific painting motion generation and sketch retargeting. Put together, the thesis forms a cohesive body of work producing human-robot paintings and making novel contributions to the fields of robot art, human-robot collaboration, and cable robot control.
- 일반주제명
- Motion capture
- 일반주제명
- Control algorithms
- 일반주제명
- Robots
- 일반주제명
- Robotics
- 기본자료저록
- Dissertations Abstracts International. 87-05B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008260126s2024 us c eng d■001000017360350
■00520260202105511
■006m o d
■007cr#unu||||||||
■020 ▼a9798263331252
■035 ▼a(MiAaPQ)AAI32308309
■035 ▼a(MiAaPQ)GeorgiaTech76869
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a000
■1001 ▼aChen, Gerry.
■24510▼aRendering, Replicating, and Adapting Human Motions on a Cable Robot for Artistic Painting
■260 ▼a[Sl]▼bGeorgia Institute of Technology▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a205 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: B.
■500 ▼aAdvisor: Dellaert, Frank;Hutchinson, Seth.
■5021 ▼aThesis (Ph.D.)--Georgia Institute of Technology, 2024.
■520 ▼aArtists have continually pushed their crafts to embody the furthest reaches of human capabilities, from delicate painting to athletic performances, highlighting the potential for robots to emulate these skills. This work aims to study the task of robot graffiti painting in three parts: rendering, replicating, and adapting human motions, ultimately contributing to the fields of robot art, cable robot control, motion planning, and generative modeling.In this work, three parts to the problem of artistic painting guided by human motions are addressed: rendering a digital artwork in paint with a cable robot; replicating human input motions as closely as possible; and adapting human input motions to accommodate for differences in level of detail, style, and artistic medium. Through the difficult, interaction-rich task of robot art, modern challenges in human-robot collaboration can be studied. In particular, techniques for robot motion control through natural input interfaces drawn from human motions are developed. Rendering paint requires advances in state estimation and control techniques for fast, fluid motions on a cable robot. Replicating human motions bridges the input motions and robot kino-dynamic capabilities, requiring advances in optima ltrajectory retiming techniques. Finally, adapting goes beyond rote replication by augmenting input motions to better fit the composition, style, and medium intended by the robot-artistteam, requiring embodiment-specific painting motion generation and sketch retargeting. Put together, the thesis forms a cohesive body of work producing human-robot paintings and making novel contributions to the fields of robot art, human-robot collaboration, and cable robot control.
■590 ▼aSchool code: 0078.
■650 4▼aMotion capture
■650 4▼aControl algorithms
■650 4▼aRobots
■650 4▼aRobotics
■690 ▼a0771
■71020▼aGeorgia Institute of Technology.
■7730 ▼tDissertations Abstracts International▼g87-05B.
■790 ▼a0078
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360350▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
