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 point cloud data and detects the locations of potential cues such as doors and rooms, (2) a circular decomposition for free 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 33.4% in simulation and 26.4% in real-world experiments.

翻译：本文提出一种自主多机器人探索流程，用于协调多房间室内环境中机器人的行为。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以系统性的方式探索并观察结构化建筑中未知的一组房间，追踪哪些房间已被探索，并在机器人之间以分布式方式共享此信息以协调其行为。为此，我们提出：（1）一种几何线索提取方法，用于处理3D点云数据并检测潜在线索（如门和房间）的位置；（2）一种用于目标分配的自由空间圆形分解方法。利用这两个组件，我们的流程有效分配机器人之间的任务，并实现对房间的系统性探索。我们使用最多3架空中机器人团队评估了流程的性能，结果表明，我们的方法在仿真中比基线方法提升33.4%，在真实世界实验中提升26.4%。