Curve Fitting-Based Dynamic Path Planning and Tracking Control for Flexible Needle Insertion

Abstract

Needle insertion is widely used in modern clinical practice, and flexible needles enable surgeons to adjust the needle insertion path to avoid obstacles and compensate for target drift. To increase the accuracy and safety of the needle insertion procedure, a path planning and tracking control method for flexible needle steering in dynamic environment is proposed in this paper. The path planning method is based on the artificial potential field algorithm and curve fitting algorithm, after several feasible paths with variant curvatures is obtained, they are furtherly optimized based on path length, obstacle clearance and control effort to select the best one. Simulations show that the proposed path planning method performs better than the current constant curvature method and the rapidly-exploring random tree (RRT) based method. By finely tuning the initial planned path, an intraoperative path replanning method is proposed, which are used to compensate for the drift of target and obstacles. Then to ensure the needle is inserted along the planned path, a tracking control method is adopted based on fuzzy logic algorithm. With the proposed intraoperative path planning and tracking control method, the robustness and accuracy of needle insertion in congested environment can be improved, and experiments also show that our proposed method achieves satisfactory insertion safety and targeting accuracy in dynamic environment. The obtained accuracy of 1.57 mm is sufficient for most clinical needle insertion applications.