Özgüner Orhan, Shkurti Thomas, Huang Siqi, Hao Ran, Jackson Russell C, Newman Wyatt S, Çavuşoğlu M Cenk
Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH.
IEEE Trans Autom Sci Eng. 2020 Oct;17(4):2154-2161. doi: 10.1109/tase.2020.2986503. Epub 2020 May 6.
The development of autonomous or semi-autonomous surgical robots stands to improve the performance of existing teleoperated equipment, but requires fine hand-eye calibration between the free-moving endoscopic camera and patient-side manipulator arms (PSMs). A novel method of solving this problem for the da Vinci® robotic surgical system and kinematically similar systems is presented. First, a series of image-processing and optical-tracking operations are performed to compute the coordinate transformation between the endoscopic camera view frame and an optical-tracking marker permanently affixed to the camera body. Then, the kinematic properties of the PSM are exploited to compute the coordinate transformation between the kinematic base frame of the PSM and an optical marker permanently affixed thereto. Using these transformations, it is then possible to compute the spatial relationship between the PSM and the endoscopic camera using only one tracker snapshot of the two markers. The effectiveness of this calibration is demonstrated by successfully guiding the PSM end effector to points of interest identified through the camera. Additional tests on a surgical task, namely grasping a surgical needle, are also performed to validate the proposed method. The resulting visually-guided robot positioning accuracy is better than the earlier hand-eye calibration results reported in the literature for the da Vinci® system, while supporting intraoperative update of the calibration and requiring only devices that are already commonly used in the surgical environment.
自主或半自主手术机器人的发展有望提升现有远程操作设备的性能,但需要在可自由移动的内窥镜摄像头与患者侧操作臂(PSM)之间进行精确的手眼校准。本文提出了一种针对达芬奇®机器人手术系统及运动学上类似系统解决此问题的新方法。首先,执行一系列图像处理和光学跟踪操作,以计算内窥镜摄像头视图框架与永久固定在摄像头主体上的光学跟踪标记之间的坐标变换。然后,利用PSM的运动学特性来计算PSM运动学基框架与永久固定在其上的光学标记之间的坐标变换。利用这些变换,仅通过两个标记的一个跟踪器快照就可以计算出PSM与内窥镜摄像头之间的空间关系。通过成功地将PSM末端执行器引导至通过摄像头识别出的感兴趣点,证明了这种校准的有效性。还对一项手术任务(即抓取手术针)进行了额外测试,以验证所提出的方法。由此产生的视觉引导机器人定位精度优于文献中报道的达芬奇®系统早期手眼校准结果,同时支持术中校准更新,并且仅需要手术环境中常用的设备。