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Article http://dx.doi.org/10.26855/acc.2024.02.008

Research on Manned and Unmanned Collaborative Mission Planning Based on Intelligent Decision-making of the ABC (Artificial Bee Colony) Algorithm

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Su Guo*, Wei Pu

Army Academy of Armored Forces, Beijing, China.

*Corresponding author: Su Guo

Published: April 9,2024

Abstract

This article delves into the realm of collaborative mission planning involving both manned and unmanned systems, leveraging the Artificial Bee Colony (ABC) Algorithm. In the context of current challenges in intelligent decision-making, especially the effective coordination of manned and unmanned entities in complex systems, this research focuses on the principles and evolution of the ABC algorithm and its role in intelligent decision-making scenarios. The study begins with a detailed analysis of the ABC algorithm's basic principles, examining its potential to facilitate collaborative planning between manned and unmanned systems. This examination leads to the construction of a specialized mission planning model tailored to the unique dynamics of such collaborations. The paper then progresses to an optimization of the ABC algorithm, aiming to heighten the efficiency and effectiveness of task planning. Anticipating a breakthrough in task planning methodologies, the study proposes a system capable of achieving optimized resource allocation and heightened decision-making efficiency in environments that involve both manned and unmanned elements. A key highlight of this research is the comprehensive analysis of the ABC algorithm's applicability in complex systems. This serves as the foundation for introducing an innovative solution, addressing the nuanced challenges faced in contemporary intelligent decision-making. This innovative approach promises to advance the field by offering new perspectives and methodologies in orchestrating collaborative missions.

References

[1] Tang J, Duan H, Lao S. Swarm intelligence algorithms for multiple unmanned aerial vehicles collaboration: A comprehensive review [J]. Artificial Intelligence Review, 2023, 56(5): 4295-4327.

[2] Zhou Y, Rao B, Wang W. UAV swarm intelligence: Recent advances and future trends [J]. IEEE Access, 2020, 8: 183856-183878.

[3] Qiming Z, Husheng W, Zhaowang F. A review of intelligent optimization algorithm applied to unmanned aerial vehicle swarm search task [C]//2021 11th International Conference on Information Science and Technology (ICIST). IEEE, 2021: 383-393.

[4] Sun W, Hao M. A Survey of Cooperative Path Planning for Multiple UAVs [C]//International Conference on Autonomous Unmanned Systems. Singapore: Springer Singapore, 2021: 189-196.

[5] Cheng Y, Li D, Wong W E, et al. Multi-UAV Collaborative Path Planning using Hierarchical Reinforcement Learning and Simulated Annealing [J]. International Journal of Performability Engineering, 2022, 18(7).

How to cite this paper

Research on Manned and Unmanned Collaborative Mission Planning Based on Intelligent Decision-making of the ABC (Artificial Bee Colony) Algorithm

How to cite this paper: Su Guo, Wei Pu. (2024) Research on Manned and Unmanned Collaborative Mission Planning Based on Intelligent Decision-making of the ABC (Artificial Bee Colony) Algorithm. Advances in Computer and Communication5(1), 48-52.

DOI: http://dx.doi.org/10.26855/acc.2024.02.008