Telerobotic and Autonomous Robotic Ultrasound Systems (RUS) help alleviate the need for operator-dependability in free-hand ultrasound examinations. However, the state-of-the-art RUSs still rely on a human operator to apply the ultrasound gel. The lack of standardization in this process often leads to poor imaging of the scanned region. The reason for this has to do with air-gaps between the probe and the human body. In this paper, we developed a end-of-arm tool for RUS, referred to as UltraGelBot. This bot can autonomously detect and dispense the gel. It uses a deep learning model to detect the gel from images acquired using an on-board camera. A motorized mechanism is also developed, which will use this feedback and dispense the gel. Experiments on phantom revealed that UltraGelBot increases the acquired image quality by $18.6\%$ and reduces the procedure time by $37.2\%$.

翻译：远程机器人及自主机器人超声系统有助于降低自由手超声检查中对操作人员的依赖。然而，当前最先进的机器人超声系统仍需依赖人工涂抹超声耦合剂。该过程缺乏标准化，常导致扫描区域成像质量不佳。其原因与探头和人体之间的空气间隙有关。本文开发了一种用于机器人超声系统的臂端工具，称为UltraGelBot。该装置能自主检测并涂布耦合剂。它采用深度学习模型，通过机载摄像头获取图像以检测耦合剂状态。同时开发了电动驱动机构，可根据反馈信息执行耦合剂涂布。体模实验表明，UltraGelBot可将获取的图像质量提升$18.6\%$，并将操作时间缩短$37.2\%$。