Path planning for flexible needle insertion system based on Improved Rapidly-Exploring Random Tree algorithm

Path planning is one of the most important parts in the research on flexible needle insertion. Based on the Improved Rapidly-exploring Random Tree (I-RRT), the path planning for flexible needle insertion is studied in this paper. Traditional RRT algorithm can generate paths which can avoid obstacle and reach the target precisely, but the path is not continuously differentiable and cannot match the physical constraints of the flexible needle inserting into soft tissue. Aiming at solving this problem, the I-RRT algorithm is proposed to generate paths for minimally invasive treatment and meanwhile guarantee the continuity and effectiveness of the path. The path evaluation function is designed to implement path selection based on path length, obstacle avoidance and the number of arcs. Then the simulation of the flexible needle path is performed in the environment with obstacles. Results show that the I-RRT is more practical and effective for flexible needle insertion path planning.