The operational environments in which a mobile robot executes its missions often exhibit non-flat terrain characteristics, encompassing outdoor and indoor settings featuring ramps and slopes. In such scenarios, the conventional methodologies employed for localization encounter novel challenges and limitations. This study delineates a localization framework incorporating ground elevation and inclination considerations, deviating from traditional 2D localization paradigms that may falter in such contexts. In our proposed approach, the map encompasses elevation and spatial occupancy information, employing Gridmaps and Octomaps. At the same time, the perception model is designed to accommodate the robot's inclined orientation and the potential presence of ground as an obstacle, besides usual structural and dynamic obstacles. We have developed and rigorously validated our approach within Nav2, and esteemed open-source framework renowned for robot navigation. Our findings demonstrate that our methodology represents a viable and effective alternative for mobile robots operating in challenging outdoor environments or intrincate terrains.

翻译：移动机器人执行任务的操作环境往往具有非平坦地形特征，包括存在坡道和斜坡的室外与室内场景。在此类场景中，传统定位方法面临新的挑战与局限性。本研究提出了一种融合地面高程与倾斜度考量的定位框架，突破了在此类环境中可能失效的传统二维定位范式。在提出的方法中，地图同时包含高程与空间占用信息，采用网格地图（Gridmaps）与八叉树地图（Octomaps）进行表征。同时，感知模型的设计兼顾了机器人的倾斜姿态，并将地面作为潜在障碍物（除常见结构障碍物与动态障碍物外）纳入考量。我们在机器人导航领域享有盛誉的开源框架Nav2中开发并严格验证了该方案。实验结果表明，该方法为运行于复杂户外环境或崎岖地形中的移动机器人提供了可行且有效的替代方案。