This work proposes an autonomous multi-robot exploration pipeline that coordinates the behaviors of robots in an indoor environment composed of multiple rooms. Contrary to simple frontier-based exploration approaches, we aim to enable robots to methodically explore and observe an unknown set of rooms in a structured building, keeping track of which rooms are already explored and sharing this information among robots to coordinate their behaviors in a distributed manner. To this end, we propose (1) a geometric cue extraction method that processes 3D map point cloud data and detects the locations of potential cues such as doors and rooms, (2) a spherical decomposition for open spaces used for target assignment. Using these two components, our pipeline effectively assigns tasks among robots, and enables a methodical exploration of rooms. We evaluate the performance of our pipeline using a team of up to 3 aerial robots, and show that our method outperforms the baseline by 36.6% in simulation and 26.4% in real-world experiments.

翻译：本文提出了一种自主多机器人探索管道，用于协调机器人在由多个房间构成的室内环境中的行为。与简单的基于前沿的探索方法不同，我们旨在使机器人能够方法性地探索并观察结构化建筑中未知的房间集合，跟踪已探索的房间并在机器人之间分布式共享此信息以协调各自行为。为此，我们提出了：（1）一种几何线索提取方法，该方法处理3D地图点云数据并检测潜在线索（如门和房间）的位置；（2）一种用于开放空间的球面分解方法，用于目标分配。利用这两个组件，我们的管道有效地在机器人之间分配任务，并实现了对房间的方法性探索。我们使用最多3台空中机器人组成的小组评估了管道的性能，并表明我们的方法在仿真中优于基线36.6%，在真实世界实验中优于基线26.4%。