자료유형 | 학위논문 |
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서명/저자사항 | Resilient Submodular Maximization for Control and Sensing. |
개인저자 | Tzoumas, Vasileios. |
단체저자명 | University of Pennsylvania. Electrical and Systems Engineering. |
발행사항 | [S.l.]: University of Pennsylvania., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 272 p. |
기본자료 저록 | Dissertation Abstracts International 79-10B(E). Dissertation Abstract International |
ISBN | 9780438037052 |
학위논문주기 | Thesis (Ph.D.)--University of Pennsylvania, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Advisers: George J. Pappas |
요약 | Fundamental applications in control, sensing, and robotics, motivate the design of systems by selecting system elements, such as actuators or sensors, subject to constraints that require the elements not only to be a few in number, but also, to |
요약 | In the first part of this thesis we motivate the above design problems, and propose the first algorithms to address them. In particular, although traditional approaches to matroid-constrained maximization have met great success in machine learni |
요약 | But in failure-prone and adversarial environments, sensors and actuators can fail |
요약 | In the second part of this thesis we motivate the general problem of resilient maximization over matroid constraints, and propose the first algorithms to address it, to protect that way any design over matroid constraints, not only within the bo |
요약 | In the third and final part of this thesis we apply our tools for resilient maximization in robotics, and in particular, to the problem of active information gathering with mobile robots. This problem calls for the motion-design of a team of mob |
일반주제명 | Electrical engineering. Systems science. Robotics. |
언어 | 영어 |
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