An Improved Path Planning Algorithm for Precise Fracture Reduction of an Orthopedic Robot

Abstract

Path planning is fundamental for controlling orthopedic robots and vital in ensuring surgical safety. To address the problem of low path-planning efficiency in traditional path planning methods, this work proposes an improved APF-RRT* algorithm for efficient path planning of fracture reduction. First, the basic RRT* algorithm is employed to expand random nodes. An artificial potential field (APF) algorithm is then integrated to improve the efficiency of path planning by guiding random node expansion and obstacle avoidance. Second, a cylindrical bounding box method is utilized for collision detection, and a Gaussian smoothing algorithm is applied to refine the optimized path, followed by collision detection of the smooth path. The performance of the improved APF-RRT* algorithm is compared with the APF-RRT*, RRT*, and A* algorithms, highlighting the superior performance of the new algorithm. Experiments conducted using a fracture reduction system validate the proposed path planning method and demonstrate that the reduction accuracy meets clinical standards, significantly enhancing the precision of the reduction operation.