Path Planning for Robot Assisted Steerable Bevel-Tip Needle in 3D Dynamic Environment

In Minimally Invasive Surgery (MIS), achieving target-reaching accuracy without colliding with anatomical obstacles is the most crucial aspect. However, due to the non-holonomic constraints within the tissue environment and the dynamic behavior during needle insertion, planning an appropriate path presents a significant and complex challenge. In order to address the above-mentioned challenges, this study introduces a novel path-planning approach for a robot-assisted flexible bevel-tip needle within the tissue region. The primary contribution of this path planner is its ability to incorporate a dynamic 3D environment, which includes multiple targets and obstacles with varying locations. In the literature, there are several methods for planning obstacle-free paths within the tissue region. Among them, the Rapidly-Exploring-Random-Trees (RRT) based path planner methodology is advantageous due to its reduced computational time and suitability for high-dimensional spaces. The proposed algorithm builds upon the RRT technique, enhancing it with a greediness concept to handle multiple dynamic targets. Additionally, extensive simulations and experimental studies have been conducted to demonstrate the efficacy of the proposed method, with a view toward future clinical tests. Statistical analysis of the proposed path planner methodology has also been performed, focusing on computational time for finding feasible paths and the length of the planned trajectory.