Abstract

The last decade has seen the eagerly anticipated introduction of marine autonomous systems as a pragmatic tool for ocean observation. However, outstanding reliability problems means that these vehicles are not yet fulfilling their true potential. Of the classes of problems, loss of communication with a marine autonomous system is both fundamental and difficult to diagnose. In our view, this is due to two reasons: first in many cases users are not technologists and secondly if a vehicle is lost the task of diagnosing the root cause is subject to epistemic uncertainty that users are often reluctant to quantify in a formal manner. As a result users may accept the first hypothesis considered as the main root cause for loss of communication. We show that this approach can result in an increased unreliability of marine autonomous systems through failure to ascertain and then address the true root causes. Consequently, we propose a probability tree approach to help diagnose root cause(s) for loss of communication with a marine autonomous system (MAS). The model was developed based on the results of two detailed investigations and a body of failure data collected from 205 undersea glider operations.

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