用RGB-D相机构建多层占位网格，提升自动驾驶车辆避障能力
Multilayer occupancy grid for obstacle avoidance in an autonomous ground vehicle using RGB-D camera
- 基于RGB-D相机构建多层成本地图，实现三维感知
- 扩展2D雷达视野，使系统具备立体障碍识别能力
- 适合研究视觉导航与自主车辆避障的开发者
本文介绍了将深度相机集成到自动驾驶地面车辆（SDV）导航系统中的过程，并实现了基于RGB-D相机的多层成本地图，将原有基于2D激光雷达的二维感知扩展为三维感知系统，显著提升了车辆对障碍物的识别能力。该方法为构建鲁棒的基于视觉的导航与障碍检测系统奠定了基础。文中还进行了理论分析，并讨论了实施结果及未来工作方向。
原文摘要 · Abstract (English)
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.
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