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An efficient surface normal estimation method is presented. The new algorithm estimates surface normal direction for each cell in a grid based on the occupancy information (both occupied and empty) of the neighboring cells. This grid representation allows user-defined sizes and scaling with the environment, not the number of measurements. Recursive and batch formulations to obtain the posterior estimate...
An iterative smoothing algorithm is developed using Gaussian mixture models in order to tackle challenging nonlinear estimation problems. Gaussian mixture models naturally capture nonlinear and non-Gaussian systems, while smoothing algorithms provide ability to update using measurements obtained in the past. A tree structure and Gaussian distribution splitting method are proposed to mitigate nonlinearity...
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