使用空地多机器人团队的距离受限覆盖控制
Range Limited Coverage Control using Air-Ground Multi-Robot Teams
AI总结：
针对异构空地多机器人团队的覆盖控制问题，提出融合多感知信息的Lloyd算法扩展方法，通过空天地机器人协同平衡局部覆盖与全局分布，经仿真和Robotarium实验验证了稳定性与性能。
摘要：
本文研究了具有不同感知能力的异构多机器人系统如何观测一个先验密度函数未知的区域。常见的覆盖控制技术针对同构机器人团队设计，并未考虑机器人感知能力差异巨大时的情况。本研究提出了一种Lloyd算法的扩展方法，融合来自具有不同感知能力的异构机器人的覆盖信息，以实现对区域的有效观测。具体而言，我们研究了由空中和地面智能体组成的双模态机器人团队。在我们的问题构建中，使用配备粗粒度区域传感器的空中机器人来估算其感知区域内实现有效覆盖所需的地面机器人数量。该信息会被传递给地面机器人，地面机器人执行改进的Lloyd算法，在局部聚焦的覆盖控制器与全局聚焦的分布控制器之间取得平衡。我们证明了该Lloyd算法扩展方法的稳定性，并通过仿真以及在Robotarium（一个可远程访问的多机器人测试平台）上开展的实验对其性能进行了评估。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
