It is challenging for the mobile robot to achieve autonomous and mapless navigation in the unknown environment with uneven terrain. In this study, we present a layered and systematic pipeline. At the local level, we maintain a tree structure that is dynamically extended with the navigation. This structure unifies the planning with the terrain identification. Besides, it contributes to explicitly identifying the hazardous areas on uneven terrain. In particular, certain nodes of the tree are consistently kept to form a sparse graph at the global level, which records the history of the exploration. A series of subgoals that can be obtained in the tree and the graph are utilized for leading the navigation. To determine a subgoal, we develop an evaluation method whose input elements can be efficiently obtained on the layered structure. We conduct both simulation and real-world experiments to evaluate the developed method and its key modules. The experimental results demonstrate the effectiveness and efficiency of our method. The robot can travel through the unknown uneven region safely and reach the target rapidly without a preconstructed map.

翻译：在未知且地形崎岖的环境中，移动机器人实现无需地图的自主导航具有挑战性。本研究提出了一种分层且系统化的流程框架。在局部层面，我们维护一个随导航过程动态扩展的树状结构。该结构将路径规划与地形识别相统一。此外，它有助于显式地识别崎岖地形上的危险区域。特别地，该树结构中的特定节点被持续保留，以在全局层面形成一个记录探索历史的稀疏图。利用可从该树状结构与图中获取的一系列子目标来引导导航。为确定子目标，我们开发了一种评估方法，其输入要素可在分层结构上高效获取。我们通过仿真与实物实验对所提方法及其关键模块进行了评估。实验结果表明了该方法的有效性与高效性。机器人能够在无需预构建地图的情况下，安全穿越未知崎岖区域并快速抵达目标。