Trajectory Planning Using Enhanced Probabilistic Roadmaps For Pliable Needle Robotic Surgery

Abstract

Trajectory planning is a necessary method in the research on pliable needle for surgical processes. Sampling-based algorithms can generate trajectories and reach the target avoiding obstacles. But the trajectories cannot match the physical constraints of injecting the pliable needle to the human flesh, as the trajectories are intermittent. Aiming at solving this problem, an enhanced Probabilistic RoadMaps [PRMs] is used in this work to solve this issue. PRM generates the trajectories for surgeries that are minimally invasive and simultaneously guarantees the effectiveness and continuity of the trajectory. In this research work, the classical PRM method is enhanced using shape preserving Piecewise Cubic Hermite Interpolation (PCHIP) technique, used to generate smooth trajectories, which are important for curved path navigation of the pliable needle for injecting in a surgery. Trajectories that have been generated using the PRM satisfy direction constraints approach on both source and target positions. As a result, the trajectories produced by the pliable needle are dynamically and geometrically feasible. Simulation results performed show the validity of the algorithm implying that it can be efficiently applied to trajectory planning of pliable needle utilizing in real-time surgical operations.