  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 $37.2\%$.
