论文标题
具有有限感应能力的动态覆盖范围的分布式策略
Distributed Strategies for Dynamic Coverage with Limited Sensing Capabilities
论文作者
论文摘要
在这项工作中，介绍了一种新颖的分布式算法的开发，该算法执行机器人覆盖范围，在静态嵌入式结构化环境中围绕事件进行聚类和调度，而无需依赖度量信息。具体而言，目的是考虑通过在涉及的每个代理上安装的可见性传感器，在封闭的未知场景中的最佳部署以及一组代理商在一个兴趣点上的重点之间的可见性传感器之间的权衡。这项研究的特定目标可以概括为1。在某些拓扑假设下，计算对所需药物数量的下限，该计算由现实的几何模型（例如圆形）提供，以强调物理局限性； 2。在连接的通信图上维持分布式方法的节点和链接的最小化； 3。识别径向降低强度的事件周围的激活群集，每个剂感受； 4。通过最大程度地减少加权等值功能的方式，将属于群集的代理发送给最强烈的点的尝试。
In this work, it is presented the development of a novel distributed algorithm performing robotic coverage, clustering and dispatch around an event in static-obstacle structured environments without relying on metric information. Specifically, the aim is to account for the trade-off between local communication given by bearing visibility sensors installed on each agent involved, optimal deployment in closed unknown scenarios and focus of a group of agents on one point of interest. The particular targets of this study can be summarized as 1. the computation, under certain topological assumptions, of a lower bound for the number of required agents, which are provided by a realistic geometric model (e.g. a round shape) to emphasize physical limitations; 2. the minimization of the number of nodes and links maintaining a distributed approach over a connected communication graph; 3. the identification of an activation cluster around an event with a radial decreasing intensity, sensed by each agent; 4. the attempt to send the agents belonging to the cluster towards the most intense point in the scenario by minimizing a weighted isoperimetric functional.
