Marine vehicles have been used for various scientific missions where information over features of interest is collected. In order to maximise efficiency in collecting information over a large search space, we should be able to deploy a large number of autonomous vehicles that make a decision based on the latest understanding of the target feature in the environment. In our previous work, we have presented a hierarchical framework for the multi-vessel multi-float (MVMF) problem where surface vessels drop and pick up underactuated floats in a time-minimal way. In this paper, we present the field trial results using the framework with a number of drifters and floats. We discovered a number of important aspects that need to be considered in the proposed framework, and present the potential approaches to address the challenges.

翻译：为了在大型搜索空间收集信息的效率最大化,我们应该能够部署大量自主车辆,根据对环境目标特征的最新了解作出决定。在先前的工作中,我们为多船多浮(MVMF)问题提出了一个分级框架,即水面船只在低时空投落并采集活性不足的浮体。在本文件中,我们利用这个框架介绍实地试验结果,并使用一些漂浮器和浮体。我们发现了一些需要在拟议框架中考虑的重要方面,并介绍了应对挑战的可能办法。