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Detecting changing traffic conditions is of primal importance for the safety of autonomous cars navigating in urban environments. Among the traffic situations that require more attention and careful planning, road junctions are the most significant. This work presents an empirical study of the application of well known machine learning techniques to create a robust method for road junction detection...
In this work, we introduce a novel method for two-dimensional occupancy mapping using Gaussian processes. We address mapping as the task of classifying the robot's environment between free and occupied regions. The biggest challenge when using Gaussian processes for this task is the size of the input datasets. We tackle this problem by introducing a novel kernel, able to use as input data aggregated...
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