Design and optimization of a haptic-feedback laparoscopic surgery simulator using particle swarm algorithm

Compared with traditional open surgery, laparoscopic surgery significantly reduces bodily trauma, postoperative pain, and hospitalization duration. However, owing to the small size of incisions and the counterintuitive motion of surgical tools, longer training cycles are required for surgeons to achieve fine operational skills. This paper presents a laparoscopic surgery simulator with haptic-feedback control (LSHC-6) that provides a reliable and cost-effective training alternative for surgeons. In addition to the structural diagram, kinematic analysis, and gravity compensation algorithm, a particle swarm optimization algorithm (PSO) is applied to optimize the structural parameters of the simulator by evaluating its workspace, global dexterity, and gravity compensation ability. A prototype system was developed and evaluated using two training experiments. The results demonstrate that the simulator exhibits good operational fluidity, workspace, and stable force output, effectively meeting the needs of laparoscopic surgical training.