Preoperative planning method based on a MOPSO algorithm for robot-assisted cholecystectomy

Surgical robots have multiple manipulators with complex mechanisms and need to work in a narrow space in the patient's body. Therefore, for robot-assisted minimally invasive surgery (RMIS), it is very important to develop a reasonable preoperative planning before surgery.

A preoperative planning method based on the premise of no collision between surgical instruments and endoscope, an evaluation index with visibility, operability and hand-eye coordination was proposed in this paper. To consider the balance relationship of global optimization index, a multi-objective particle swarm optimization (MOPSO) algorithm was adopted. Because the physical characteristics of each patient are different, the method can determine the selectable area of the incision based on the relevant knowledge of anatomy.

The simulation taking the cholecystectomy as an example was performed on a minimally invasive surgical robotic system. The analysis result showed that the proposed preoperative planning method based on the MOPSO could provide surgeons with a reasonable and effective preoperative planning.

The proposed preoperative planning method based on the MOPSO is suitable for patients with different physical characteristics, and can provide a guidance for surgeons and effectively reduce the preoperative planning time and improve the safety and efficiency of the operation, especially a novice surgeon who lacks robot-assisted minimally invasive surgery experience.