This paper presents a probabilistic framework for unmarked roads estimation using radar sensors. The algorithm models the sensor likelihood function as a Gaussian mixture model. This sensor likelihood is used in a Bayesian approach to estimate the road edges probability…

In this paper we present a scalable machine learning approach to mobile robots visual localization. The applicability of machine learning approaches is constrained by the complexity and size of the problem’s domain. Thus, dividing the problem becomes necessary and two…