Autonomous path planning for robot-assisted pelvic fracture closed reduction with collision avoidance

Robot-assisted pelvic fracture closed reduction (RPFCR) positively contributes to patient treatment. However, the current path planning suffers from incomplete obstacle avoidance and long paths.A collision detection method is proposed for applications in the pelvic environment to improve the safety of RPFCR surgery. Meanwhile, a defined orientation planning strategy (OPS) and linear sampling search (LSS) are coupled into the A* algorithm to optimise the reduction path. Subsequently, pelvic in vitro experimental platform is built to verify the augmented A*algorithm's feasibility.The augmented A* algorithm planned the shortest path for the same fracture model, and the paths planned by the A* algorithm and experience-based increased by 56.12% and 89.02%, respectively.The augmented A* algorithm effectively improves surgical safety and shortens the path length, which can be adopted as an effective model for developing RPFCR path planning.