用言语化决策树状态解释自治
Towards Explaining Autonomy with Verbalised Decision Tree States
摘要：
新的AUV技术的发展增加了AUV可以处理的任务范围和操作长度。因此，AUV能够处理高度复杂的操作。然而，这些任务并不容易适合传统的方法，即将任务定义为一系列预先计划的航路点，因为不可能提前知道任务期间可能发生的一切。这导致运营商的期望与实际运营绩效之间存在差距。因此，这会降低操作员和AUV之间的信任度，导致不必要的任务中断。为了弥合任务中机器人行为与操作员期望之间的差距，这项工作旨在提供一个框架，以易于理解的方式解释自主车辆在任务期间所采取的决定和行动。此外，我们的目标是拥有一个独立的自治系统，可以作为任何自治架构之上的附加层添加。为了使该方法适用于不同的自治系统配备了不同的知识，这项工作从决策点和所产生的执行动作应用知识蒸馏的自治的内部工作。最后，为了以更自然的方式向操作员呈现解释，将提取的决策树的输出与自然语言解释组合，并将其作为句子报告给操作员。出于这个原因，在解释管道的末尾添加了一个称为Concept2Text Generation的额外步骤。
英文摘要：
The development of new AUV technology increased the range of tasks that AUVs can tackle and the length of their operations. As a result, AUVs are capable of handling highly complex operations. However, these missions do not fit easily into the traditional method of defining a mission as a series of pre-planned waypoints because it is not possible to know, in advance, everything that might occur during the mission. This results in a gap between the operator's expectations and actual operational performance. Consequently, this can create a diminished level of trust between the operators and AUVs, resulting in unnecessary mission interruptions. To bridge this gap between in-mission robotic behaviours and operators' expectations, this work aims to provide a framework to explain decisions and actions taken by an autonomous vehicle during the mission, in an easy-to-understand manner. Additionally, the objective is to have an autonomy-agnostic system that can be added as an additional layer on top of any autonomy architecture. To make the approach applicable across different autonomous systems equipped with different autonomies, this work decouples the inner workings of the autonomy from the decision points and the resulting executed actions applying Knowledge Distillation. Finally, to present the explanations to the operators in a more natural way, the output of the distilled decision tree is combined with natural language explanations and reported to the operators as sentences. For this reason, an additional step known as Concept2Text Generation is added at the end of the explanation pipeline.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
