Highly accurate and robust localization ability is of great importance for autonomous
vehicles (AVs) in urban scenarios. Traditional vision-based methods suffer from lost due to …

Easy, yet robust long-term localization is still an open topic in research. Existing approaches
require either dense maps, expensive sensors, specialized map features or proprietary …

In this letter, we propose a method for accurately estimating the 6-Degree Of Freedom (DOF)
pose in an urban environment when a High Definition (HD) map is available. An HD map …

Localization in aerial imagery-based maps offers many advantages, such as global
consistency, geo-referenced maps, and the availability of publicly accessible data. However …

While complete localization approaches are widely studied in the literature, their data
association and data representation subprocesses usually go unnoticed. However, both are …

The idea of cooperative perception is to benefit from shared perception data between
multiple vehicles and overcome the limitations of on-board sensors on single vehicle …

In this article, a high-accuracy real-time vector map matching method based on polynomial
fitting is proposed for autonomous driving. The real-time kinematic (RTK) positioning …

Feature-based geo-localization relies on associating features extracted from aerial imagery
with those detected by the vehicle's sensors. This requires that the type of landmarks must …

Robust visual localization in traffic scenes is a fundamental problem for self-driving vehicles.
However, it is still challenging to achieve accurate localization performance because of …

Feature-based geo-localization relies on associating features extracted from aerial imagery
with those detected by the vehicle's sensors. This requires that the type of landmarks must …