Cooperative multi-task assignment for heterogonous UAVs

Name: Cooperative multi-task assignment for heterogonous UAVs
Author: Özalp, N., Ayan, U., Öztop, Erhan

İsim	Cooperative multi-task assignment for heterogonous UAVs
Yazar	Özalp, N., Ayan, U., Öztop, Erhan
Basım Tarihi:	2015
Basım Yeri	- IEEE
Konu	Task assignment, Genetic algorithm, UAV, Heuristic task assignment, Cooperative task, Agent
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-146737509-2
Kayıt Numarası	a819a9ac-0417-4c3c-be50-33ed1e6dd255
Lokasyon	Computer Science
Tarih	2015
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	This research is focused on the cooperative multi-task assignment problem for heterogeneous UAVs, where a set of multiple tasks, each requiring a predetermined number of UAVs, have to be completed at specific locations. We modeled this as an optimization problem to minimize the number of uncompleted tasks while also minimizing total airtime and total distance traveled by all the UAVs. By taking into account the UAV flight capacities. For the solution of the problem, we adopted a multi-Traveling Salesman Problem (mTSP) method [1] and designed a new genetic structure for it so that it can be applied to cooperative multi-task assignment problems. Furthermore, we developed two domain specific mutation operators to improve the quality of the solutions in terms of number of uncompleted tasks, total airtime and total distance traveled by all the UAVs. The simulation experiments showed that these operators significantly improve the solution quality. Our main contributions are the application of the Multi Structure Genetic Algorithm (MSGA) to cooperative multi-task assignment problem and the development of two novel mutation operators to improve the solution of MSGA.
DOI	10.1109/ICAR.2015.7251517

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Cooperative multi-task assignment for heterogonous UAVs

Yazar Özalp, N., Ayan, U., Öztop, Erhan

Basım Tarihi 2015

Basım Yeri - IEEE

Konu Task assignment, Genetic algorithm, UAV, Heuristic task assignment, Cooperative task, Agent

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-146737509-2

Kayıt Numarası a819a9ac-0417-4c3c-be50-33ed1e6dd255

Lokasyon Computer Science

Tarih 2015

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin This research is focused on the cooperative multi-task assignment problem for heterogeneous UAVs, where a set of multiple tasks, each requiring a predetermined number of UAVs, have to be completed at specific locations. We modeled this as an optimization problem to minimize the number of uncompleted tasks while also minimizing total airtime and total distance traveled by all the UAVs. By taking into account the UAV flight capacities. For the solution of the problem, we adopted a multi-Traveling Salesman Problem (mTSP) method [1] and designed a new genetic structure for it so that it can be applied to cooperative multi-task assignment problems. Furthermore, we developed two domain specific mutation operators to improve the quality of the solutions in terms of number of uncompleted tasks, total airtime and total distance traveled by all the UAVs. The simulation experiments showed that these operators significantly improve the solution quality. Our main contributions are the application of the Multi Structure Genetic Algorithm (MSGA) to cooperative multi-task assignment problem and the development of two novel mutation operators to improve the solution of MSGA.

DOI 10.1109/ICAR.2015.7251517