The main task in navigation of an autonomous vehicle is to have accurate and robust localization. There are variety of localization techniques in study using particle filter; for localization with or without using map information in the measurements. There is a lack of study in localization methods employing map data in particle filter. This paper summarizes the localization techniques that use map information in particle filter for estimation. The study of various literature in the particle filter for localization using map data shows that, accurate and robust localization can be achieved for an autonomous vehicle provided the map to be used in the measurements is constructed precisely with the necessary features like road curbs, edges, trajectories etc.
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Map-Based Particle Filter for Localization: Autonomous Vehicle
Semantic Scholar · Engineering · 2020
Abstract
The main task in navigation of an autonomous vehicle is to have accurate and robust localization. There are variety of localization techniques in study using particle filter; for localization with or without using map information in the measurements. There is a lack of study in localization methods employing map data in particle filter. This paper summarizes the localization techniques that use map information in particle filter for estimation. The study of various literature in the particle filter for localization using map data shows that, accurate and robust localization can be achieved for an autonomous vehicle provided the map to be used in the measurements is constructed precisely with the necessary features like road curbs, edges, trajectories etc.