A flexible topological representation consisting of a two-layer graph structure built on-board an Unmanned Aerial Vehicle (UAV) by continuously filling the free space of an occupancy map with intersecting spheres is proposed in this \paper{}. Most state-of-the-art planning methods find the shortest paths while keeping the UAV at a pre-defined distance from obstacles. Planning over the proposed structure reaches this pre-defined distance only when necessary, maintaining a safer distance otherwise, while also being orders of magnitude faster than other state-of-the-art methods. Furthermore, we demonstrate how this graph representation can be converted into a lightweight shareable topological-volumetric map of the environment, which enables decentralized multi-robot cooperation. The proposed approach was successfully validated in several kilometers of real subterranean environments, such as caves, devastated industrial buildings, and in the harsh and complex setting of the final event of the DARPA SubT Challenge, which aims to mimic the conditions of real search and rescue missions as closely as possible, and where our approach achieved the \nth{2} place in the virtual track.
翻译:由两层图解结构组成的灵活的表层代表结构,该结构在无人驾驶飞行器(UAV)上通过不断填充空闲空间,填充具有交叉空间的占用图,在本文件中提出。大多数最先进的规划方法找到最短路径,同时将无人驾驶飞行器保持在预先确定的距离之外。对拟议结构的规划仅在必要的时候达到预先确定的距离,否则则保持更安全的距离,同时比其他最先进的方法更快,同时我们展示如何将这个图形代表制转换成一个轻量的、可分享的环境表层材料图,从而能够分散多机器人合作。提议的方法在数公里的实际次次地环境(如洞穴、被破坏的工业建筑)和DARPA SubT 挑战最后事件的严酷和复杂环境中成功验证,目的是尽可能地模拟实际搜索和救援任务的条件,并在虚拟轨道上实现我们的方法。