Optimizing Variable Admittance Control for Remote Ultrasound Scanning Under Uncertain Environment

Precise force control in remote robotic ultrasound systems is critical for optimizing image quality and ensuring patient safety. However, conventional admittance control strategies face limitations in achieving high-precision force tracking during interaction while maintaining accurate position tracking in free motion. To address this challenge, we propose an adaptive variable admittance approach integrated with a novel coarse-to-fine force control strategy, which requires online estimation of environmental properties. The environmental information is estimated by a fusion algorithm that combines force and position data from sensors with confidence scores derived from ultrasound images. Furthermore, a compensation term is introduced to the variable stiffness control law to mitigate estimation uncertainties, thereby enhancing force tracking accuracy. Additionally, an energy tank mechanism is implemented to guarantee system passivity under varying damping and stiffness conditions. The effectiveness of the proposed method was experimentally validated using a teleoperated ultrasound system, tested on both a vascular phantom model and human upper limb. The proposed controller demonstrated stable force tracking performance while maintaining compliance throughout the interaction process. The force tracking errors were maintained within ranges of 0.2 N and 0.4 N with standard deviation of 0.02 N and 0.2 N for the phantom and human experiments, respectively.