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Task Allocation of Multi-AUVs Based on Innovative Auction Algorithm

Authors: Ziying Zhang; Jie Wang; Dong Xu 0010; Yulong Meng;

Task Allocation of Multi-AUVs Based on Innovative Auction Algorithm

Abstract

Based on task allocation of multi-AUV (Autonomous Underwater Vehicle) system, the innovative auction algorithm is applied to hunting task assignments of multi-AUV. The two most decisive factor in the auction algorithm: the election of the auctioneer and the calculation of bidding value. In the traditional auction algorithm, the auctioneer's choice follows the principle of "Who finds the target, who is the auctioneer", but this principle seriously threatens the security and robustness of auction process of the multi-AUV. We propose a new method to determine auctioneer and the method of determining the bidding value of multiple AUV in the auction algorithm, and we have made an essential optimization of the auction algorithm. The final experimental results show that the optimized auction algorithm is compared with the traditional auction algorithm and other hunting tasks allocation algorithms, the security and robustness of the innovative auction has a better effect.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Top 10%
Average
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