Autonomous underwater vehicle (AUV) plays an important role in ocean research. Compared with single AUV system, multi-AUV system has higher stability, robustness and high efficiency. Multiple AUVs give greater credibility than a single AUV in decision making. In this paper, the problem of multiple AUV making dangerous decisions in dangerous environments is studied. Single AUV can not make an accurate decision when facing some complex situations. We propose to fuse multiple AUV data to obtain more accurate dangerous decisions. The multi-AUV system adopts a distributed multi-robot structure, each AUV is an individual. A transferable information model and Dempster-Shafer evidence theory are used. A new multi-AUV hazard discrimination model is proposed for the final hazard decisionmaking. Verification by calculation, new decision-making method can effectively improve the discriminant ability of multi-AUV system when facing danger. This new hazard decision method improves the survivability of multiple AUVs in actual ocean exploration.

中文翻译：

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基于信息融合的多水下机器人危险性决策方法

自主水下航行器（AUV）在海洋研究中起着重要作用。与单AUV系统相比，多AUV系统具有更高的稳定性，鲁棒性和高效率。在决策过程中，多个AUV比单个AUV具有更高的信誉。本文研究了多种AUV在危险环境下做出危险决策的问题。当遇到某些复杂情况时，单个AUV无法做出准确的决定。我们建议融合多个AUV数据以获得更准确的危险决策。多AUV系统采用分布式多机器人结构，每个AUV都是独立的。使用了可转移信息模型和Dempster-Shafer证据理论。针对最终危险决策，提出了一种新的多AUV危险判别模型。通过计算验证 新的决策方法可以有效地提高多AUV系统在面临危险时的判别能力。这种新的危险决策方法提高了多个AUV在实际海洋勘探中的生存能力。