Autonomous UUV control via tunably decentralized algorithms

K.M. Sullivan, S. Luke
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引用次数: 2

Abstract

We apply previous studied control algorithms to the cooperative target observation (CTO) task for multiple UUVs. The algorithms are based on k-means clustering and hill climbing, and each are scalable in the degree of decentralization. In the underwater formulation of the CTO problem, k-means is not sensitive to the degree of decentralization, while the hill climber is sensitive. Unlike in previous work, K-means outperformed hill-climbing across all environmental parameters.
自主UUV控制通过可调分散算法
我们将前人研究的控制算法应用于多uv的协同目标观测任务。这些算法基于k-means聚类和爬坡算法,每个算法在去中心化程度上都是可扩展的。在CTO问题的水下表述中,k-means对分散化程度不敏感,而爬山者则敏感。与之前的研究不同,K-means在所有环境参数上都优于爬山。
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