LAUSR

Surgical robots have increased in popularity, and their performance is closely related to the robotic positioning before surgery. Many recent studies in preoperative planning have focused on the pose selection of the robot and the port placement. However, it is difficult to position the surgical robot simply based on experience. To solve this problem, the surgical workspace is subdivided into several subspaces with different weights. Global isotropy index and cooperation capability index are proposed to reflect the performance of the surgical robot and used as optimization functions. Particle swarm optimization is used to optimize the setup parameters. Based on different weight distributions, setup parameters can be automatically given and sent to the simulation system to display the setup and guide the robot positioning. The results show that the setup optimization considering the internal diversity of workspace is capable of satisfying the detailed requirements of robotic surgery and effectively guide the robotic surgery setup.