论文标题
自动无人机网络的连接感知信息素移动性模型
Connectivity-Aware Pheromone Mobility Model for Autonomous UAV Networks
论文作者
论文摘要
无人机网络包括降低，重量和功率（低掉期）固定翼无人机，用于平民和军事应用，例如搜索和救援，监视和跟踪。为了有效地执行这些操作，有必要开发具有高网络连接性的可扩展，分散的自主无人机网络体系结构。但是，区域覆盖范围和网络连接要求表现出基本的权衡。在本文中，连接感知的信息素移动性（CAP）模型是为搜索和救援操作而设计的，该模型能够维持网络中无人机之间的连通性。我们使用基于Stigmergy的数字信息素地图以及基于距离的本地连接信息来自主协调UAV运动，以提高其地图覆盖效率，同时保持高网络连接。
UAV networks consisting of reduced size, weight, and power (low SWaP) fixed-wing UAVs are used for civilian and military applications such as search and rescue, surveillance, and tracking. To carry out these operations efficiently, there is a need to develop scalable, decentralized autonomous UAV network architectures with high network connectivity. However, the area coverage and the network connectivity requirements exhibit a fundamental trade-off. In this paper, a connectivity-aware pheromone mobility (CAP) model is designed for search and rescue operations, which is capable of maintaining connectivity among UAVs in the network. We use stigmergy-based digital pheromone maps along with distance-based local connectivity information to autonomously coordinate the UAV movements, in order to improve its map coverage efficiency while maintaining high network connectivity.
