With the increasing demand for mobile robots and autonomous vehicles, several approaches for long-term robot navigation have been proposed. Among these techniques, ground segmentation and traversability estimation play important roles in perception and path planning, respectively. Even though these two techniques appear similar, their objectives are different. Ground segmentation divides data into ground and non-ground elements; thus, it is used as a preprocessing stage to extract objects of interest by rejecting ground points. In contrast, traversability estimation identifies and comprehends areas in which robots can move safely. Nevertheless, some researchers use these terms without clear distinction, leading to misunderstanding the two concepts. Therefore, in this study, we survey related literature and clearly distinguish ground and traversable regions considering four aspects: a) maneuverability of robot platforms, b) position of a robot in the surroundings, c) subset relation of negative obstacles, and d) subset relation of deformable objects.

翻译：随着移动机器人与自动驾驶车辆需求的日益增长，多种长期机器人导航方法已被提出。在这些技术中，地面分割与可通行性估计分别对感知和路径规划起着关键作用。尽管这两项技术看似相似，但其目标有所区别。地面分割将数据划分为地面与非地面元素，因此作为预处理阶段通过剔除地面点来提取感兴趣目标。相比之下，可通行性估计旨在识别和理解机器人能够安全移动的区域。然而，部分研究者在使用这些术语时未作明确区分，导致对这两个概念的误解。为此，本研究系统梳理相关文献，并基于以下四个方面清晰区分地面与可通行区域：a) 机器人平台的可操纵性，b) 机器人在环境中的位置，c) 负障碍物的子集关系，以及d) 可变形物体的子集关系。