This work describes the process of integrating a depth camera into the navigation system of a self-driving ground vehicle (SDV) and the implementation of a multilayer costmap that enhances the vehicle's obstacle identification process by expanding its two-dimensional field of view, based on 2D LIDAR, to a three-dimensional perception system using an RGB-D camera. This approach lays the foundation for a robust vision-based navigation and obstacle detection system. A theoretical review is presented and implementation results are discussed for future work.

翻译：本研究阐述了将深度相机集成到自动驾驶地面车辆导航系统的过程，以及多层代价地图的实现方法。该方法通过将基于2D LIDAR的二维视场扩展为使用RGB-D相机的三维感知系统，增强了车辆的障碍物识别能力。此方法为构建鲁棒的视觉导航与障碍物检测系统奠定了基础。文中进行了理论综述，并讨论了实现结果以指导后续研究工作。