通过实时局部代价地图更新改进面向农业应用的ROS 2导航栈
Improving the ROS 2 Navigation Stack with Real-Time Local Costmap Updates for Agricultural Applications
AI总结：
本文提出一种轻量级方法，利用深度摄像头进行像素级分类并实时校正Nav2局部代价地图，使机器人能穿越高草等户外障碍物，在Clearpath Husky上验证了其能完成标准组件无法实现的导航任务。
摘要：
ROS 2 Navigation Stack (Nav2) 已成为一种广泛使用的软件组件，为开发各种高级功能提供了底层基础。然而，当在果园和葡萄园等户外环境中使用时，其功能明显受到室内环境中不常见的障碍物和/或情况的限制。一个这样的例子是高草和杂草，机器人可以安全地穿过它们，但LiDAR传感器可能会将其感知为障碍物，从而迫使机器人采取更长的路径来避开它们，或者完全中止导航。为了克服这些限制，必须开发特定领域的扩展并将其集成到软件流程中。本文提出了一种新的轻量级方法来应对这一挑战并改进户外机器人导航。利用支持Nav2的代价地图的多尺度特性，我们开发了一个系统，该系统使用深度摄像头对图像执行像素级分类，并实时将校正注入局部代价地图，从而使机器人能够穿越原本会被Nav2避开的区域。我们的方法已在Clearpath Husky上实现并得到验证，我们证明通过此扩展，机器人能够执行使用标准组件原本不切实际的导航任务。
英文摘要：
The ROS 2 Navigation Stack (Nav2) has emerged as a widely used software component providing the underlying basis to develop a variety of high-level functionalities. However, when used in outdoor environments such as orchards and vineyards, its functionality is notably limited by the presence of obstacles and/or situations not commonly found in indoor settings. One such example is given by tall grass and weeds that can be safely traversed by a robot, but that can be perceived as obstacles by LiDAR sensors, and then force the robot to take longer paths to avoid them, or abort navigation altogether. To overcome these limitations, domain specific extensions must be developed and integrated into the software pipeline. This paper presents a new, lightweight approach to address this challenge and improve outdoor robot navigation. Leveraging the multi-scale nature of the costmaps supporting Nav2, we developed a system that using a depth camera performs pixel level classification on the images, and in real time injects corrections into the local cost map, thus enabling the robot to traverse areas that would otherwise be avoided by the Nav2. Our approach has been implemented and validated on a Clearpath Husky and we demonstrate that with this extension the robot is able to perform navigation tasks that would be otherwise not practical with the standard components.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
