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Yayın Stochastic surface mesh reconstruction(International Society for Photogrammetry and Remote Sensing, 2018-05-30) Özendi, Mustafa; Akça, Mehmet Devrim; Topan, HüseyinA generic and practical methodology is presented for 3D surface mesh reconstruction from the terrestrial laser scanner (TLS) derived point clouds. It has two main steps. The first step deals with developing an anisotropic point error model, which is capable of computing the theoretical precisions of 3D coordinates of each individual point in the point cloud. The magnitude and direction of the errors are represented in the form of error ellipsoids. The following second step is focused on the stochastic surface mesh reconstruction. It exploits the previously determined error ellipsoids by computing a point-wise quality measure, which takes into account the semi-diagonal axis length of the error ellipsoid. The points only with the least errors are used in the surface triangulation. The remaining ones are automatically discarded.Yayın Co-registration of 3d point clouds by using an errors-in-variables model(Copernicus Gesellschaft MBH, 2012-08-25) Aydar, Umut; Altan, Mehmet Orhan; Akyılmaz, Orhan; Akça, Mehmet DevrimCo-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In the literature, one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D least squares (LS) matching methods as well. In most of the co-registration methods, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values. This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a new method where the stochastic properties of both (template and search) surfaces are considered under an errors-in-variables (EIV) model. The experiments have been carried out using a close range laser scanning data set and the results of the conventional and EIV types of the ICP matching methods have been compared.Yayın Maintenance policy simulation for a factored partially observable system(The Society for Modeling and Simulation International, 2019-07) Özgür Ünlüakın, Demet; Kıvanç, İpekTaking maintenance decisions is one of the well-known stochastic sequential decision problems under uncertainty. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for such problems. Nevertheless, POMDPs are rarely used for tackling maintenance problems of multi-component systems because their state spaces grow exponentially with the increasing number of components. Factored representations have been proposed for POMDPs taking advantage of the factored structure already available in the nature of the problem. Our aim in this study is to show how to formulate a factored POMDP model for the maintenance problem of a multi-component dynamic system and how to simulate and evaluate the obtained policy before implementing it in real life. The sensitivity of the methodology is analyzed under several cost values, and the methodology is compared to other predefined policies. The results show that the policies generated via the POMDP solver perform better than the predefined policies.
