Supervised autonomy for AUVs using limited bandwidth communication channels

该项目旨在改善机器人平台和操作员之间的反馈链接，以提高水下测量作业的有效性。在调查期间，需要一定程度的适应，以使水下机器人能够对它们正在收集的数据做出反应。通常很难对自主系统进行可靠的编程，以识别显著数据，特别是当任务涉及搜索传感器特征可能难以确定先验的特定特征时。相比之下，人类通常擅长快速识别重要数据或确定任务何时没有实现目标。该项目旨在开发新的声学通信方案，利用机器学习、网络和通信理论的发展，实现人类操作员和水下机器人之间的通信。

This project aims to improve the feedback link between robotic platforms and an operator, to increase the effectiveness of underwater survey operations. During surveys, some level of adaptation is required to allow underwater robots to respond to the data they are collecting. It is often difficult to reliably program an autonomous system to identify salient data, particularly when the mission involves searching for particular features whose sensor signatures may be difficult to determine a priori. In contrast, humans are generally good at quickly identifying important data or determining when a mission is not achieving its goals. The project aims to develop novel acoustic communication schemes that will allow communication between the human operator and the underwater robot, exploiting developments in machine learning, network and communication theory.