Cooperative Task Planning for Multiple Autonomous UAVs with Graph Representation and Genetic Algorithm

被引：0
|
作者：
Geng, L. [1 ]
Zhang, Y. F. [1 ]
Wang, J. J. [1 ]
Fuh, J. Y. H. [1 ]
Teo, S. H. [2 ]
机构：
[1] Natl Univ Singapore, Dept Mech Engn, Singapore 117548, Singapore
[2] DSO Natl Labs, Singapore, Singapore
来源：
2013 10TH IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION (ICCA) | 2013年
关键词：
SEARCH; ALLOCATION;
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：
This paper addresses the mission planning issues for guiding a group of UAVs to carry out a series of tasks, namely classification, attack, and verification, against multiple targets. The flying space is constrained with the presence of flight prohibit zones (FPZs) and enemy radar sites. The solution space for task assignment and sequencing is modeled with a graph representation. With a path formation based on Dubins vehicle paths, a genetic algorithm (GA) has been developed for finding the optimal solution from the graph to achieve the following goals: (1) completion of the three tasks on each target, (2) avoidance of FPZs, (3) low level of exposure to enemy radar detection, and (4) short overall flying path length. A case study is presented to demonstrate the effectiveness of the proposed methods.
引用
收藏
页码：394 / 399
页数：6
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