A Survey of Autonomous Robotic Ultrasound Scanning Systems

This review investigates recent advancements in autonomous, semi-autonomous, and teleoperated robotic ultrasound systems. Traditional ultrasound imaging depends on manual probe manipulation, which introduces operator variability, physical strain, and limitations in accessibility. To address these challenges, this review investigates recent advancements in autonomous, semi-autonomous, and teleoperated robotic ultrasound systems by analyzing over 60 publications, including key developments from 2022 to 2025. Our survey reveals a growing adoption of cobot-based solutions equipped with 6-DOF force/torque sensors and RGB-D vision systems for precise probe positioning. Notably, several systems now integrate reinforcement learning, image-guided visual servoing, and real-time feedback loops to enable intelligent trajectory planning and adaptive force control. However, we identify critical gaps in the literature: surface-parallel force and torque components are often ignored in control models, limiting the accuracy of probe orientation and tissue coupling. Furthermore, real-time ultrasound image feedback is rarely used for path optimization, despite its importance in enhancing image quality and diagnostic reliability. This review emphasizes the need for future systems to integrate multi-modal sensing, adaptive control, and real-time image quality assessment to achieve robust, generalizable robotic ultrasound workflows.