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Title: Gaussian random field-based log odds occupancy mapping
Authors: Li, Hongjun
Barão, Miguel
Rato, Luís
Keywords: Gaussian Processes
Robot mapping
Issue Date: 24-May-2018
Publisher: IEEE
Citation: Li H., Barão M., Rato L., "Gaussian random field-based log odds occupancy mapping", In 2018 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), May 24-26, 2018, Cluj-Napoca, Romania.
Abstract: This paper focuses on mapping problem with known robot pose in static environments and proposes a Gaussian random field-based log odds occupancy mapping (GRF-LOOM). In this method, occupancy probability is regarded as an unknown parameter and the dependence between parameters are considered. Given measurements and the dependence, the parameters of not only observed space but also unobserved space can be predicted. The occupancy probabilities in log odds form are regarded as a GRF. This mapping task can be solved by the well-known prediction equation in Gaussian processes, which involves an inverse problem. Instead of the prediction equation, a new recursive algorithm is also proposed to avoid the inverse problem. Finally, the proposed method is evaluated in simulations.
Type: lecture
Appears in Collections:INF - Comunicações - Em Congressos Científicos Internacionais

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