DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Jinwhan | - |
dc.contributor.advisor | 김진환 | - |
dc.contributor.author | Jonsson, Thorsteinn Baldvin | - |
dc.date.accessioned | 2019-08-28T02:43:02Z | - |
dc.date.available | 2019-08-28T02:43:02Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=828453&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/265839 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 기계공학과, 2018.8,[v, 39 p. :] | - |
dc.description.abstract | Many natural phenomena can be represented by scalar fields and being able to quickly and efficiently construct an estimate of them is crucial in environmental monitoring. This study proposes an adaptive path planning algorithm for efficient scalar field reconstruction with a mobile robotic platform. By exploiting the underlying field characteristics, the path planning module focuses the sampling on informative areas that lead to a more accurate reconstruction. Sampling locations are optimized with Bayesian optimization and Gaussian process regression models the underlying field based on sampled data. Furthermore, a new acquisition function is proposed in the Bayesian optimization framework to guide the search for a more efficient solution in terms of path length and mission duration. The proposed method is compared to a commonly used exhaustive coverage path planning algorithm through numerous simulations on synthetic data and results are shown that indicate that the proposed method converges to an accurate solution significantly faster. Finally, the feasibility of real-life applications is shown in a comprehensive simulation that utilizes data collected from a natural phenomenon. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Adaptive path planning▼agaussian process▼abayesian optimization | - |
dc.subject | 적응적 경로계획▼a가우시안 프로세스▼a베이지안 최적화 | - |
dc.title | Informative path planning with gaussian processes for efficient scalar field reconstruction | - |
dc.title.alternative | 효율적인 스칼라장 재구성을 위한 가우시안 프로세스 기반의 정보적 경로 계획 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :기계공학과, | - |
dc.contributor.alternativeauthor | 존슨 토르스테인 발드빈 | - |
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