Barducci Lavinia, Scaglioni Bruno, Martin James, Obstein Keith L, Valdastri Pietro
STORM Lab United Kingdom, Institute of Robotics, Autonomous Systems and Sensing, School of Electronic and Electrical Engineering, University of Leeds, Leeds, United Kingdom.
STORM Lab United States, Vanderbilt University Medical Center, Nashville, TN, United States.
Front Robot AI. 2022 Apr 14;9:854081. doi: 10.3389/frobt.2022.854081. eCollection 2022.
Magnetically actuated robots have become increasingly popular in medical endoscopy over the past decade. Despite the significant improvements in autonomy and control methods, progress within the field of medical magnetic endoscopes has mainly been in the domain of enhanced navigation. Interventional tasks such as biopsy, polyp removal, and clip placement are a major procedural component of endoscopy. Little advancement has been done in this area due to the problem of adequately controlling and stabilizing magnetically actuated endoscopes for interventional tasks. In the present paper we discuss a novel Linear Parameter Varying (LPV) control approach to provide stability during interventional maneuvers. This method linearizes the non-linear dynamic interaction between the external actuation system and the endoscope in a set of equilibria, associated to different distances between the magnetic source and the endoscope, and computes different controllers for each equilibrium. This approach provides the global stability of the overall system and robustness against external disturbances. The performance of the LPV approach is compared to an intelligent teleoperation control method (based on a Proportional Integral Derivative (PID) controller), on the Magnetic Flexible Endoscope (MFE) platform. Four biopsies in different regions of the colon and at two different system equilibria are performed. Both controllers are asked to stabilize the endoscope in the presence of external disturbances (i.e. the introduction of the biopsy forceps through the working channel of the endoscope). The experiments, performed in a benchtop colon simulator, show a maximum reduction of the mean orientation error of the endoscope of 45.8 with the LPV control compared to the PID controller.
在过去十年中，磁驱动机器人在医学内窥镜检查中越来越受欢迎。尽管在自主性和控制方法方面有了显著改进，但医用磁内窥镜领域的进展主要集中在增强导航方面。活检、息肉切除和夹子放置等介入性任务是内窥镜检查的主要程序组成部分。由于在介入性任务中充分控制和稳定磁驱动内窥镜存在问题，该领域进展甚微。在本文中，我们讨论了一种新颖的线性参数变化（LPV）控制方法，以在介入操作过程中提供稳定性。该方法在一组与磁源和内窥镜之间不同距离相关的平衡点处，将外部驱动系统与内窥镜之间的非线性动态相互作用线性化，并为每个平衡点计算不同的控制器。这种方法提供了整个系统的全局稳定性和对外部干扰的鲁棒性。在磁柔性内窥镜（MFE）平台上，将LPV方法的性能与智能遥操作控制方法（基于比例积分微分（PID）控制器）进行了比较。在结肠的不同区域以及两个不同的系统平衡点处进行了四次活检。要求两个控制器在存在外部干扰（即通过内窥镜的工作通道引入活检钳）的情况下稳定内窥镜。在台式结肠模拟器中进行的实验表明，与PID控制器相比，LPV控制使内窥镜的平均方向误差最大降低了45.8。
