SAM: Semi-Active Mechanism for Extensible Continuum Manipulator and Real-time Hysteresis Compensation Control Algorithm
This addresses control accuracy issues in surgical robots for minimally invasive procedures, offering incremental improvements in hysteresis compensation.
The paper tackled hysteresis in Cable-Driven Continuum Manipulators (CDCMs) for scar-free surgery by introducing an extensible CDCM with a Semi-active Mechanism (SAM) and a real-time hysteresis compensation control algorithm using a Temporal Convolutional Network (TCN). The result showed a reduction in hysteresis by up to 69.5% in trajectory tracking and approximately 26% in box pointing tasks.
Cable-Driven Continuum Manipulators (CDCMs) enable scar-free procedures but face limitations in workspace and control accuracy due to hysteresis. We introduce an extensible CDCM with a Semi-active Mechanism (SAM) and develop a real-time hysteresis compensation control algorithm using a Temporal Convolutional Network (TCN) based on data collected from fiducial markers and RGBD sensing. Performance validation shows the proposed controller significantly reduces hysteresis by up to 69.5% in random trajectory tracking test and approximately 26% in the box pointing task. The SAM mechanism enables access to various lesions without damaging surrounding tissues. The proposed controller with TCN-based compensation effectively predicts hysteresis behavior and minimizes position and joint angle errors in real-time, which has the potential to enhance surgical task performance.