Kim, Soohwan; Kim, Jonghyuk
This paper proposes a new method for building occupancy maps using Dirichlet and Gaussian processes. We consider occupancy map building as a classification problem and apply Gaussian processes. The main drawback of Gaussian processes, however, is the computational complexity of O(n3) related to the matrix inversion, where n is the number of data points. To enable large-scale occupancy map building, we propose to use Dirichlet process mixture models which cluster input data without fixing the...[Show more]
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