In autonomous robotics, a critical challenge lies in developing robust solutions for Active Collaborative SLAM, wherein multiple robots collaboratively explore and map an unknown environment while intelligently coordinating their movements and sensor data acquisitions. In this article, we present an approach for coordinating a system consisting of multiple robots to perform Active Collaborative SLAM (AC-SLAM) for environmental exploration. Our method efficiently spreads the robots for maximum exploration while keeping SLAM uncertainty low. Additionally, We also present two coordination approaches, synchronous and asynchronous to prioritize robot goal assignments by the central server. The proposed method is implemented in ROS and evaluated through simulation and experiments on publicly available datasets and similar methods, rendering promising results.

翻译：在自主机器人领域，一个关键挑战在于开发用于主动协作式SLAM（Active Collaborative SLAM, AC-SLAM）的鲁棒解决方案，其中多台机器人协作探索并绘制未知环境地图，同时智能协调其运动与传感器数据采集。本文提出了一种协调多机器人系统以执行主动协作式SLAM进行环境探索的方法。我们的方法在保持SLAM低不确定性的同时，高效分散机器人以实现最大程度的探索。此外，我们还提出了两种协调方法——同步与异步方式，由中央服务器对机器人的目标分配进行优先级排序。所提方法在ROS中实现，并通过在公开数据集上与类似方法进行的仿真与实验进行评估，取得了良好结果。