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.

翻译：自动驾驶车辆需要精确且鲁棒的定位与建图算法，以确保在城市环境中安全可靠地行驶。我们提出了一种新颖的基于传感器融合的管线，用于基于LiDAR传感器的离线建图和在线定位。所提出方法利用了四个LiDAR传感器。建图和定位算法基于KISS-ICP，可实现实时性能和高精度。我们引入了一种方法，用于生成面向路径规划等驾驶任务的语义地图。所提出的管线已集成到基于ROS 2的Autoware软件栈中，为自动驾驶应用提供了鲁棒且灵活的环境。我们证明，针对给定的研究车辆和真实世界自动驾驶应用，我们的管线优于现有最先进方法。