Mapping, as the back-end of perception and the front-end of path planning in the modern UAV navigation system, draws our interest. Considering the requirements of UAV navigation and the features of the current embedded computation platforms, we designed and implemented a novel multilayer mapping framework. In this framework, we divided the map into three layers: awareness, local, and global. The awareness map is constructed in cylindrical coordinate, enabling fast raycasting. The local map is a probability-based volumetric map. The global map adopts dynamic memory management, allocating memory for the active mapping area, and recycling the memory from the inactive mapping area. We implemented this mapping framework in three parallel threads: awareness thread, local-global thread, and visualization thread. Finally, we evaluated the mapping kit in both the simulation environment and the real-world scenario with the vision-based sensors. The framework supports different kinds of map outputs for the global or local path planners. The implementation is open-source for the research community.

中文翻译：

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自主无人机导航的多层映射套件

作为现代无人机导航系统中感知的后端和路径规划的前端，制图引起了我们的兴趣。考虑到无人机导航的要求和当前嵌入式计算平台的功能，我们设计并实现了一种新颖的多层映射框架。在此框架中，我们将地图分为三层：意识层，本地层和全局层。感知图是在圆柱坐标系中构建的，可以进行快速射线广播。局部图是基于概率的体积图。全局映射采用动态内存管理，为活动的映射区域分配内存，并从非活动的映射区域回收内存。我们在三个并行线程中实现了此映射框架：感知线程，局部全局线程和可视化线程。最后，我们使用基于视觉的传感器在仿真环境和实际场景中评估了映射套件。该框架为全局或局部路径计划者支持不同类型的地图输出。该实现对研究社区是开源的。