In the realm of autonomous robotics, a critical challenge lies in developing robust solutions for Active Collaborative SLAM, wherein multiple robots must collaboratively explore and map an unknown environment while intelligently coordinating their movements and sensor data acquisitions. To this aim, we present two approaches for coordinating a system consisting of multiple robots to perform Active Collaborative SLAM (AC-SLAM) for environmental exploration. Our two coordination approaches, synchronous and asynchronous implement a methodology to prioritize robot goal assignments by the central server. We also present a method to efficiently spread the robots for maximum exploration while keeping SLAM uncertainty low. Both coordination approaches were evaluated through simulation on publicly available datasets, obtaining promising results.

翻译：在自主机器人领域，核心挑战在于开发用于主动协同SLAM的鲁棒解决方案——多机器人需在未知环境中协同探索与建图，同时智能协调其运动与传感器数据采集。为此，我们提出两种方法来协调多机器人系统执行主动协同SLAM（AC-SLAM）以实现环境探索。我们的两种协调方法（同步与异步）实现了由中央服务器优先分配机器人目标的机制。同时，我们提出了一种在保持SLAM不确定性较低的前提下，高效分散机器人以实现最大探索范围的方法。两种协调方法均通过公开数据集的仿真实验进行了评估，获得了具有前景的结果。