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A Learning-based Approach to Safety for Uncertain Robotic Systems
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | A Learning-based Approach to Safety for Uncertain Robotic Systems. |
| 개인저자 | Akametalu, Anayo K. |
| 단체저자명 | University of California, Berkeley. Electrical Engineering & Computer Sciences. |
| 발행사항 | [S.l.]: University of California, Berkeley., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 95 p. |
| 기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
| ISBN | 9780438325012 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Berkeley, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Claire J. Tomlin. |
| 요약 | Robotic 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 |
| 요약 | This 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 |
| 일반주제명 | Electrical engineering. Computer science. Robotics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
