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Review of Dynamic Task Allocation Methods for UAV Swarms Oriented to Ground Targets

Authors :
Qiang Peng
Husheng Wu
Ruisong Xue
Source :
Complex System Modeling and Simulation, Vol 1, Iss 3, Pp 163-175 (2021)
Publication Year :
2021
Publisher :
Tsinghua University Press, 2021.

Abstract

Dynamic task allocation of unmanned aerial vehicle swarms for ground targets is an important part of unmanned aerial vehicle (UAV) swarms task planning and the key technology to improve autonomy. The realization of dynamic task allocation in UAV swarms for ground targets is very difficult because of the large uncertainty of swarms, the target and environment state, and the high real-time allocation requirements. Hence, dynamic task allocation of UAV swarms oriented to ground targets has become a key and difficult problem in the field of mission planning. In this work, a dynamic task allocation method for UAV swarms oriented to ground targets is comprehensively and systematically summarized from two aspects: the establishment of an allocation model and the solution of the allocation model. First, the basic concept and trigger scenario are introduced. Second, the research status and the advantages and disadvantages of the two allocation models are analyzed. Third, the research status and the advantages and disadvantages of several common dynamic task allocation algorithms, such as the algorithm based on market mechanisms, intelligent optimization algorithm, and clustering algorithm, are evaluated. Finally, the specific problems of the current UAV swarm dynamic task allocation method for ground targets are highlighted, and future research directions are established. This work offers important reference significance for fully understanding the current situation of UAV swarm dynamic task allocation technology.

Details

Language :
English
ISSN :
20969929
Volume :
1
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Complex System Modeling and Simulation
Publication Type :
Academic Journal
Accession number :
edsdoj.632ee1599573499794c875ce29716a75
Document Type :
article
Full Text :
https://doi.org/10.23919/CSMS.2021.0022