A novel model-based path planning method for robot-assisted flexible needle insertion

In needle insertion procedures, path planning is crucial to the success of the operation. In this paper, a preoperative path planning algorithm is proposed that considers the needle-tissue interactions for flexible needle insertion operations. Vector Form Intrinsic Finite Element (VFIFE) and Finite Element Method (FEM) are used to calculate the deformation of the needle and tissue, respectively. The non-linearity of the needle and the change of boundary conditions during the insertion process can be integrated easily. The Potential Field-guided Rapidly-Exploring Random Trees (PF-RRT) is applied to generate the initial path set, in which the candidate path will be selected. The needle control sequence that is to generate the optimal path is obtained from the selected candidate path by combining Iteration Learning Control (ILC) method with the needle-tissue interaction model. The simulation results show that the proposed method is effective to generate candidate needle insertion paths that consider needle-tissue interactions.