Multi-UAV Routing for Persistent Intelligence Surveillance & Reconnaissance Missions

被引：0

作者：

Manyam, Satyanarayana G. ^{[1
]}

Rasmussen, Steven ^{[2
]}

Casbeer, David W. ^{[1
]}

Kalyanam, Krishnamoorthy ^{[3
]}

Manickam, Suresh ^{[4
]}

机构：

[1] US Air Force, Res Lab, Wright Patterson AFB, OH 45433 USA

[2] Miami Valley Aerosp LLC, US Air Force, Res Lab, Wright Patterson AFB, OH USA

[3] InfoSciTex Corp, Dayton, OH USA

[4] DRDO, Aeronaut Dev Establishment, Bangalore, Karnataka, India

来源：

2017 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS'17) | 2017年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We consider a Persistent Intelligence, Surveillance and Reconnaissance (PISR) routing problem, which includes collecting data from a set of specified task locations and delivering that data to a control station. Each task is assigned a refresh rate based on its priority, where higher priority tasks require higher refresh rates. The UAV team's objective is to minimize the maximum of the delivery times of all the tasks' data to the control station, while simultaneously, satisfying each task's revisit period constraint. The centralized path planning problem for this PISR routing problem is formulated using mixed integer linear programming and solved using a branch-and-cut algorithm. Heuristics are presented to find suboptimal feasible solutions that require much less computation time. The algorithms are tested on several instances and their performance is compared with respect to the optimal cost and computation time.

引用

页码：573 / 580

页数：8

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