Multi-robot coverage is crucial in numerous applications, including environmental monitoring, search and rescue operations, and precision agriculture. In modern applications, a multi-robot team must collaboratively explore unknown spatial fields in GPS-denied and extreme environments where global localization is unavailable. Coverage algorithms typically assume that the robot positions and the coverage environment are defined in a global reference frame. However, coordinating robot motion and ensuring coverage of the shared convex workspace without global localization is challenging. This paper proposes a novel anchor-oriented coverage (AOC) approach to generate dynamic localized Voronoi partitions based around a common anchor position. We further propose a consensus-based coordination algorithm that achieves agreement on the coverage workspace around the anchor in the robots' relative frames of reference. Through extensive simulations and real-world experiments, we demonstrate that the proposed anchor-oriented approach using localized Voronoi partitioning performs as well as the state-of-the-art coverage controller using GPS.

翻译：多机器人覆盖在环境监测、搜救行动和精准农业等众多应用中至关重要。在现代应用中，多机器人团队必须在全球定位不可用的无GPS极端环境中协作探索未知空间场域。传统覆盖算法通常假设机器人位置和覆盖环境定义在全局参考系中。然而，在没有全局定位的情况下协调机器人运动并确保共享凸工作空间的覆盖具有挑战性。本文提出一种新颖的基于锚点的覆盖方法，围绕公共锚点位置生成动态局部化Voronoi划分。我们进一步提出基于共识的协调算法，在机器人相对参考系中就锚点周围的覆盖工作空间达成一致。通过大量仿真和实际实验，我们证明所提出的基于锚点的局部化Voronoi划分方法在性能上可与使用GPS的最先进覆盖控制器相媲美。