Vision-Based Surgical Tool Pose Estimation for the da Vinci Robotic Surgical System.

This paper presents an approach to surgical tool tracking using stereo vision for the da Vinci Surgical Robotic System. The proposed method is based on robot kinematics, computer vision techniques and Bayesian state estimation. The proposed method employs a silhouette rendering algorithm to create virtual images of the surgical tool by generating the silhouette of the defined tool geometry under the da Vinci robot endoscopes. The virtual rendering method provides the tool representation in image form, which makes it possible to measure the distance between the rendered tool and real tool from endoscopic stereo image streams. Particle Filter algorithm employing the virtual rendering method is then used for surgical tool tracking. The tracking performance is evaluated on an actual da Vinci surgical robotic system and a ROS/Gazebo-based simulation of the da Vinci system.