  Autonomous vehicles require accurate and robust localization and mapping
algorithms to navigate safely and reliably in urban environments. We present a
novel sensor fusion-based pipeline for offline mapping and online localization
based on LiDAR sensors. The proposed approach leverages four LiDAR sensors.
Mapping and localization algorithms are based on the KISS-ICP, enabling
real-time performance and high accuracy. We introduce an approach to generate
semantic maps for driving tasks such as path planning. The presented pipeline
is integrated into the ROS 2 based Autoware software stack, providing a robust
and flexible environment for autonomous driving applications. We show that our
pipeline outperforms state-of-the-art approaches for a given research vehicle
and real-world autonomous driving application.
