Multi-UAV task assignment based on improved Wolf Pack Algorithm

Chen, Haowen; Xu, Jinyu; Wu, Chao

doi:10.1145/3444370.3444556

Cited by 2 publications

(1 citation statement)

References 5 publications

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“…The algorithm exhibit improved optimality and efficiency in generating assignment results, enhancing the probability of converging to the optimal solution. Luo et al [75] presented a solution to maximize completion time and minimize total task time by considering the function or function level of UAVs and time constraints. They introduced a multi-swarm fruit fly optimization algorithm with a two-strategy switching mechanism.…”

Section: Other Algorithmsmentioning

confidence: 99%

Survey on Collaborative Task Assignment for Heterogeneous UAVs Based on Artificial Intelligence Methods

Li,

Shao

et al. 2024

CAAI Artificial Intelligence Research

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Heterogeneous unmanned aerial vehicle (UAV) swarms have garnered significant attention from researchers worldwide due to their remarkable flexibility, diverse mission capabilities, and wide-ranging potential applications. Mission planning stands at the core of UAV swarm operations, requiring consideration of various factors including mission environment, requirements, and inherent characteristics. In this paper, we investigate the model of the cooperative tasking problem in heterogeneous UAV swarms. We provide a comprehensive review of artificial intelligence algorithms applied in UAV swarm mission planning, analyzing their strengths and weaknesses in multi-UAV cooperative environments. By discussing these key techniques and their practical applications, the article highlights future research trends and challenges. This review serves as a valuable reference for understanding the current state of AI algorithm applications in heterogeneous UAV swarm task assignments.

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Section: Other Algorithmsmentioning

confidence: 99%

Survey on Collaborative Task Assignment for Heterogeneous UAVs Based on Artificial Intelligence Methods

Li,

Shao

et al. 2024

CAAI Artificial Intelligence Research

View full text Add to dashboard Cite

show abstract

A Review of Task Allocation Methods for UAVs

Skaltsis,

Shin,

Tsourdos

2023

J Intell Robot Syst

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Unmanned aerial vehicles, can offer solutions to a lot of problems, making it crucial to research more and improve the task allocation methods used. In this survey, the main approaches used for task allocation in applications involving UAVs are presented as well as the most common applications of UAVs that require the application of task allocation methods. They are followed by the categories of the task allocation algorithms used, with the main focus being on more recent works. Our analysis of these methods focuses primarily on their complexity, optimality, and scalability. Additionally, the communication schemes commonly utilized are presented, as well as the impact of uncertainty on task allocation of UAVs. Finally, these methods are compared based on the aforementioned criteria, suggesting the most promising approaches.

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Multi-UAV task assignment based on improved Wolf Pack Algorithm

Cited by 2 publications

References 5 publications

Survey on Collaborative Task Assignment for Heterogeneous UAVs Based on Artificial Intelligence Methods

Survey on Collaborative Task Assignment for Heterogeneous UAVs Based on Artificial Intelligence Methods

A Review of Task Allocation Methods for UAVs

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