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A Learning-based Approach to Safety for Uncertain Robotic Systems

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자료유형학위논문
서명/저자사항A Learning-based Approach to Safety for Uncertain Robotic Systems.
개인저자Akametalu, Anayo K.
단체저자명University of California, Berkeley. Electrical Engineering & Computer Sciences.
발행사항[S.l.]: University of California, Berkeley., 2018.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2018.
형태사항95 p.
기본자료 저록Dissertation Abstracts International 80-01B(E).
Dissertation Abstract International
ISBN9780438325012
학위논문주기Thesis (Ph.D.)--University of California, Berkeley, 2018.
일반주기 Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Claire J. Tomlin.
요약Robotic systems are becoming more pervasive, and have the potential to significantly improve human lives. However, for these benefits to be realized it is critical that the safe operation of these systems be guaranteed. Reachability analysis has
요약This thesis uses Hamilton-Jacobi (HJ) reachability analysis to robustly guarantee safety for systems with uncertainty. In the presence of uncertainty there must be a balance between conservativeness as it pertains to safety and performance as it
일반주제명Electrical engineering.
Computer science.
Robotics.
언어영어
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