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

基于实时有限元仿真和交叉熵优化的柔性针高精度自主控制

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Abstract

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 ex vivo 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.

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