Global localization is an important and widely studied problem for many robotic applications.
Place recognition approaches can be exploited to solve this task, eg, in the autonomous …

In this work, we present MapLite: a one-click autonomous navigation system capable of
piloting a vehicle to an arbitrary desired destination point given only a sparse publicly …

Cross-modal vehicle localization is an important task for automated driving systems. This
research proposes a novel approach based on LiDAR point clouds and OpenStreetMaps …

Detecting buildings in the surroundings of an urban vehicle and matching them to building
models available on map services is an emerging trend in robotics localization for urban …

In this paper we propose a probabilistic approach for detecting and classifying urban road
intersections from a moving vehicle. The approach is based on images from an onboard …

Wi-Fi-based localization has many advantages for personal mobile devices as it works well
indoors or in urban environments while consuming much less energy than global …

For accurate vehicle self-localization, many approaches rely on the match between
sophisticated 3D map data and sensor information obtained from laser scanners or camera …

LiDAR odometry enables localising vehicles and robots in the environments where global
navigation satellite systems (GNSS) are not available. An inherent limitation of LiDAR …

As an important component in transportation maps, three-dimensional (3D) structure
information of grade-separated junctions is crucial for applications such as intelligent …

In this paper we present a probabilistic lane-localization algorithm for highway-like
scenarios designed to increase the accuracy of the vehicle localization estimate. The …