在機器人輔助之遠端操縱手術中,主控制設備和從端機器人之間的運動縮放比例是克服人類生理限制的使系統提高精度的關鍵特徵之一。通過適當地調整運動縮放因子,可以使外科醫生精確地執行精細的手術或有效率地到達遠處的目標。然而,在手術過程中手動調整運動縮放因子會使醫生嚴重分散注意力。許多研究已經著手於這個問題,並提出了自動調整運動縮放因子的方法。但是,這些方法需要大量的負擔來決定自動調整縮放因子中的適當參數。本文提出了一種基於人為操作模型的運動縮放因子之參數設計的方法。此外,我們將提出的算法與虛擬導引技術相整合以及時生成適當的觸覺回饋,並進一步提高外科醫生執行手術時的準確性和效率。該方法在由 4 自由度之力回饋裝置和腹腔手術機器人所組成的機器人外科手術系統上得到了證明。實驗結果表明,與手動調整和其他自動調整的方法相比,所提出的自動調整運動縮放因子之方法在執行臨床前外科手術任務時具有更高的效率。
In robot-assisted teleoperated surgery, the motion scaling ratio between the master control device and the slave robotic manipulator is one of the critical features to improve the precision of manipulation against human physiological limitations. By properly adjusting the motion scaling factor, the surgeon is allowed to either precisely perform a delicate operation or to efficiently reach a distant target. However, it is distracting to manually tune the motion scaling factor during the surgical tasks. Several methods have addressed this issue and proposed auto-tuned motion scaling. However, these methods require significant efforts in the determination of the adequate parameters used in the auto-tuning algorithm. In this thesis, we propose a framework to systematically design the motion scaling auto-tuner based on human operation model. Besides, we integrate the proposed algorithm with the formulation of virtual fixtures, which generates adequate real-time haptic feedback to further improve the accuracy and time-efficiency when the surgeon performs surgical tasks. The proposed method is demonstrated on a robotic surgical system composed of a 4-degree-of-freedom (4-DOF) haptic-enabled control device and the LapaRobot-a robotic surgical system designed for telementoring and training in laparoscopic surgery. The experimental results show that the auto-tuned motion scaling achieves better time-efficiency in performing pre-clinical surgical tasks, compared with manual-tuned and other auto-tuned approaches.