High-Precision Autonomous Control of Flexible Needles via Real-Time Finite Element Simulation and Cross-Entropy Optimization

This paper presents a unified framework for autonomous flexible needle control in soft tissues using real-time finite element (FE) simulation and cross-entropy (CE) optimization. The method combines a sampling-based model predictive controller (MPC) for trajectory tracking with a kinematic-based bang-bang strategy to coordinate needle insertion, lateral adjustments, and bevel rotations. Sparse electromagnetic (EM) tracking feedback enables needle state reconstruction and compensates for model uncertainties. Experiments in plastisol and <i>ex vivo</i> chicken breast phantoms show sub-millimeter targeting accuracy, with respective targeting errors 0.16 ± 0.29 mm and 0.22 ± 0.78 mm as reported by the tracker.