Confidence-Driven Adaptive Optimal Impedance Control Base on Ultrasound Robot System

Abstract

The ultrasound robotic system (URS) is of tremendous importance for assisting sonographers to diagnose various diseases. Generally, the quality of ultrasound image which is evaluated through confidence map has a high dependency on the experience of sonographers. In order to obtain high-quality ultrasound image under URS, we take confidence map into consideration of control frame and propose confidence-driven adaptive optimal impedance learning scheme. By introducing an appropriate performance function which blends both confidence value and contacting force, an iterative learning strategy is conducted to achieve favorable scanning performance. Finally, we show the experiment results on the human volunteer.