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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.01193 |
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| _version_ | 1866912805318295552 |
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| author | Feng, Zixin Xue, Wenchao Mu, Yifen Wei, Ming Meng, Bin Cui, Wei |
| author_facet | Feng, Zixin Xue, Wenchao Mu, Yifen Wei, Ming Meng, Bin Cui, Wei |
| contents | This paper focuses on the optimal coverage problem (OCP) for multi-agent systems with a decentralized optimization mechanism. A game based distributed decision-making method for the multi-agent OCP is proposed to address the high computational costs arising from the large scale of the multi-agent system and to ensure that the game's equilibrium achieves the global performance objective's maximum value. In particular, a distributed algorithm that needs only local information is developed and proved to converge to near-optimal global coverage. Finally, the proposed method is applied to maximize the coverage area of the UAV network for a target region. The simulation results show that our method can require much less computational time than other typical distributed algorithms in related work, while achieving a faster convergence rate. Comparison with centralized optimization also demonstrates that the proposed method has approximate optimization results and high computation efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_01193 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On Game based Distributed Approach for General Multi-agent Optimal Coverage with Application to UAV Networks Feng, Zixin Xue, Wenchao Mu, Yifen Wei, Ming Meng, Bin Cui, Wei Systems and Control This paper focuses on the optimal coverage problem (OCP) for multi-agent systems with a decentralized optimization mechanism. A game based distributed decision-making method for the multi-agent OCP is proposed to address the high computational costs arising from the large scale of the multi-agent system and to ensure that the game's equilibrium achieves the global performance objective's maximum value. In particular, a distributed algorithm that needs only local information is developed and proved to converge to near-optimal global coverage. Finally, the proposed method is applied to maximize the coverage area of the UAV network for a target region. The simulation results show that our method can require much less computational time than other typical distributed algorithms in related work, while achieving a faster convergence rate. Comparison with centralized optimization also demonstrates that the proposed method has approximate optimization results and high computation efficiency. |
| title | On Game based Distributed Approach for General Multi-agent Optimal Coverage with Application to UAV Networks |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2408.01193 |