In this paper, we investigate how heterogeneous multi-robot systems with different sensing capabilities can observe a domain with an apriori unknown density function. Common coverage control techniques are targeted towards homogeneous teams of robots and do not consider what happens when the sensing capabilities of the robots are vastly different. This work proposes an extension to Lloyd's algorithm that fuses coverage information from heterogeneous robots with differing sensing capabilities to effectively observe a domain. Namely, we study a bimodal team of robots consisting of aerial and ground agents. In our problem formulation we use aerial robots with coarse domain sensors to approximate the number of ground robots needed within their sensing region to effectively cover it. This information is relayed to ground robots, who perform an extension to the Lloyd's algorithm that balances a locally focused coverage controller with a globally focused distribution controller. The stability of the Lloyd's algorithm extension is proven and its performance is evaluated through simulation and experiments using the Robotarium, a remotely-accessible, multi-robot testbed.

翻译：在本文中，我们研究了具有不同感知能力的异构多机器人系统如何观测具有先验未知密度函数的域。常见的覆盖控制技术针对同质机器人团队，未考虑机器人感知能力差异巨大的情形。本文提出了Lloyd算法的扩展，融合来自具有不同感知能力的异构机器人的覆盖信息，以实现对域的有效观测。具体而言，我们研究由空中和地面智能体组成的双模态机器人团队。在问题建模中，我们利用具有粗粒度域传感器的空中机器人估算其感知区域内所需的地面机器人数量以实现有效覆盖。此信息被传递给地面机器人，后者执行Lloyd算法的扩展——在局部聚焦覆盖控制器与全局聚焦分布控制器之间取得平衡。证明了该Lloyd算法扩展的稳定性，并通过使用远程可访问的多机器人实验平台Robotarium进行仿真与实验评估其性能。