膝關節手術機器人之微創型鉗制法開發

Development of a Less Invasive Clamper for Knee Surgical Robot

劉士鳴(Shih-Ming Liu)

指導教授 ： 顏炳郎

國立臺北科技大學/機電學院/自動化科技研究所/碩士(2009年)

摘要

在手術過程中，施行手術之病體的骨頭部位在空間中的移動，會造成與手術機器人之間相對關係的變化，為了偵測出此三維的變化量並進行補償，使得骨頭與機器手臂之相對關係維持固定，本研究提出應用於膝關節置換手術輔助機器人的影像伺服系統，此影像伺服系統採用了雙CCD相機建立之立體視覺系統，並藉由追蹤被動式標靶(passive optical tracker)上的特徵點，來偵測骨頭在空間中的位移量以進行補償，同時本系統採用以位置為基礎(position-based)與ECL(endpoint closed-loop)的影像伺服架構，除了將該被動式標靶附加於膝關節上的骨釘外，也附加於機器手臂的末端效應器(end effector)上，並在手術過程中，藉由追蹤標靶來進行動態校準，獲得手術輔助機器人與骨頭座標系相對於相機之間的轉換關係，進而得知骨頭與機器手臂之間的相對關係，動態地改變手術機器人的位置以達到動態補償的目的，透過本方法可大幅降低骨頭固定方式的侵入性，相較於其他手術方法，本方法可明顯降低因骨頭移動，以及機構參數不夠準確，所造成之手術精度誤差。

關鍵字

骨頭動態校準 ； 全膝關節置換手術 ； 微創型鉗制法 ； 立體視覺系統 ； 影像伺服

並列摘要

During the operation, the moving of patient always cause the change of the position between surgical robot and anatomical object (femur or tibia, for example), this change is dynamic and three-dimensional. For fix the change dynamically, This paper proposes a visual servo control method to compensate the anatomical object movement. This visual servo control system includes two CCD cameras and two passive optical markers to establish the stereo visual system. By tracking the feature points on optical tracker, the movement of bone or end-effector (or tooltip) of robot in Cartesian space can be observed. The visual servo system is position-based visual servo control using ECL (endpoint closed-loop) structure. By tracking the optical markers attached on bone or tooltip, the position and pose of those could be known dynamically. The transformation between the bone and tooltip can be obtained dynamically. The servo system will be actuated so that the position and pose between these two frames can be remained.

並列關鍵字

Total Knee Replacement ； stereo vision system ； dynamic registration ； visual servo control ； invasive clamper

參考文獻

[3] F. Chassat & S.Lavallee, Experimental Protocol of Accuracy Evaluation of 6-D Localizers for Computer-Integrated Surgery: Application to four Optical Localizers, Heidelberg: Springer Berlin, 1998, pp. 277–284.

[6] H.W. When and P.R. Beranger. “Ultrasound-Based Robot Position Estimation, “ IEEE Transactions on Robotics and Automation, vol. 13, 1997, pp. 682-692.

[7] K.R. Smith, K.J. Frank, and R.D. Bucholz. “The Neurostation: a highly accurate minimally invasive solution to frameless stereotactic neurosurgery,” Computerized Medical Imaging and Graphics, vol. 18, 1994, pp. 247-256.

[8] S. Hutchinson, G. Hager, P. Corke, “A tutorial on visual vervo control,” IEEE Transactions on Robotics and Automation, vol. 12, no. 5, 1996, pp. 651-670.

[10] S. Arun, T.S. Huang & S.D. Blostein, “Least-Squares Fitting of two 3-D point Sets,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 5, 1987.