Joint route planning for UAV and sensor network for data retrieval

P. Sujit, D. Lucani, J. Sousa
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引用次数: 20

Abstract

Large scale data gathering from remote sensor networks is a key issue in many remote deployments. Manual data collection is difficult and sending ground robots to collect information can be complex due to uneven terrain. Alternately, unmanned aerial vehicle (UAV) can be used to collect data from sensor networks. The UAV will fly over the sensors gathering the data. However, to minimize the flight time of the UAV and maximize the network lifetime, a joint route optimization for UAV and sensor network must be carried out. Additionally, the UAV has kinematic constraints and communication range limitations. Determining solution with these constraints is difficult and computationally intensive. In this paper, we propose a heuristic solution by decoupling the problem into four sub-problems. The first is to determine clusters of sensors with communication range limitations. The second is to efficiently connect the clusters. The third is to design the route inside the cluster that will maximize the information collection and the fourth is to design a path planner for the UAV for data collection. We show the proposed solution through an example.
面向数据检索的无人机与传感器网络联合航路规划
在许多远程部署中,从遥感网络中大规模采集数据是一个关键问题。人工采集数据困难,由于地形不平坦,派遣地面机器人采集信息可能会很复杂。另外,无人驾驶飞行器(UAV)可以用于从传感器网络收集数据。无人机将飞越传感器收集数据。然而,为了最小化无人机的飞行时间和最大化网络寿命,必须对无人机和传感器网络进行联合航路优化。此外,无人机具有运动学约束和通信距离限制。确定具有这些约束的解是困难的,并且计算量很大。在本文中,我们提出了一种启发式解决方案,将问题解耦为四个子问题。首先是确定具有通信范围限制的传感器集群。二是高效连接集群。三是设计集群内部的路径,使信息收集最大化;四是为无人机设计路径规划器,进行数据收集。我们通过一个例子来展示所提出的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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