Recent advances in robotic ultrasound systems have shown promise for improving diagnostic imaging consistency. However, maintaining stable contact force across dynamic physiological changes (e.g., breathing, tremors) without continuous sensor recalibration remains a critical hurdle. "By integrating a hybrid active-passive force control mechanism, our method decouples force regulation from real-time feedback dependencies while ensuring adaptability across patients," stated corresponding author Qingsong Xu, a professor at the University of Macau. The tripartite system combines (a) a passive constant-force mechanism (positive/negative stiffness beams) for vibration buffering, (b) strain gauges for real-time deformation monitoring, and (c) active positioning stages for gravity compensation and force adjustment. "This design guarantees force stability by absorbing high-frequency disturbances passively while actively compensating for sustained displacements," added lead author Zehao Wu.
The framework was validated in experiments with silicone models and human subjects under simulated physiological vibrations. The passive mechanism achieved ≤7.20% force variation within its constant-force region (adjustable range: 12.33–21.29 N), isolating tremors of up to 15 Hz frequency and tolerating breathing-induced displacements (0.3 Hz, 6 mm amplitude). Active control maintained force consistency across inclinations (e.g., 1.11 N gravity compensation at 25° tilt), while robotic operation reduced image oscillation velocities by >50% compared to manual scans (0.55 mm/s vs. >1.0 mm/s). Compared to pure active force control, the hybrid system eliminated overshoot risks and reduced reliance on high-bandwidth sensors.
"Strain-based feedback enabled precise tuning of the constant-force zone, synchronizing probe contact with tissue compliance," noted Wu. Limitations include restricted force-range coverage (12–21 N) and mechanism size constraints. Future work will develop multi-range mechanisms and integrate semi-autonomous path planning. This study advances medical robotics by fusing mechanical intelligence with adaptive control, enabling robust, operator-agnostic ultrasound imaging.
Authors of the paper include Zehao Wu, Xianli Wang, Yuning Cao, Weijian Zhang, and Qingsong Xu.
This work was supported in part by the National Natural Science Foundation of China under grant 52175556; the Macao Science and Technology Development Fund under grants 0004/2022/AKP, 0102/2022/A2, 0078/2023/RIB3, and 0047/2024/ITP2; and the University of Macau under grants MYRG-GRG2024-00222-FST-UMDF and MYRG-CRG2022-00004-FST-ICI.
The paper, "Robotic Ultrasound Scanning End-Effector with Adjustable Constant Contact Force" was published in the journal Cyborg and Bionic Systems on May 2 2025, at DOI: 10.34133/cbsystems.0251.
