3D scene graphs have recently emerged as an expressive high-level map representation that describes a 3D environment as a layered graph where nodes represent spatial concepts at multiple levels of abstraction (e.g., objects, rooms, buildings) and edges represent relations between concepts (e.g., inclusion, adjacency). This paper describes Hydra-Multi, the first multi-robot spatial perception system capable of constructing a multi-robot 3D scene graph online from sensor data collected by robots in a team. In particular, we develop a centralized system capable of constructing a joint 3D scene graph by taking incremental inputs from multiple robots, effectively finding the relative transforms between the robots' frames, and incorporating loop closure detections to correctly reconcile the scene graph nodes from different robots. We evaluate Hydra-Multi on simulated and real scenarios and show it is able to reconstruct accurate 3D scene graphs online. We also demonstrate Hydra-Multi's capability of supporting heterogeneous teams by fusing different map representations built by robots with different sensor suites.

翻译：三维场景图最近作为一种高表达性的高层次地图表示方式出现，它将三维环境描述为分层图结构，其中节点表示多个抽象层级（例如物体、房间、建筑物）的空间概念，边表示概念之间的关系（例如包含、邻接）。本文介绍了Hydra-Multi，这是首个能够根据团队中机器人收集的传感器数据在线构建多机器人三维场景图的多机器人空间感知系统。具体而言，我们开发了一个集中式系统，能够通过输入多个机器人的增量数据，有效计算各机器人坐标系间的相对变换，并融合闭环检测结果以正确协调来自不同机器人的场景图节点。我们在模拟和真实场景中评估了Hydra-Multi，结果表明该系统能够在线重建准确的三维场景图。我们还通过融合搭载不同传感器套件的机器人构建的多样地图表示，展示了Hydra-Multi支持异构机器人团队的能力。