Building occupancy maps with a mixture of Gaussian processes
This paper proposes a new method for occupancy map building using a mixture of Gaussian processes. We consider occupancy maps as a binary classification problem of positions being occupied or not, and apply Gaussian processes. Particularly, since the computational complexity of Gaussian processes grows as O(n3), where n is the number of data points, we divide the training data into small subsets and apply a mixture of Gaussian processes. The procedure of our map building method consists of...[Show more]
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