Markov Intent-Driven Shared Control for Teleoperated Needle Puncture

This paper presents a probabilistic shared-control framework for teleoperated robotic needle puncture to mitigate tracking latency and the 'pop-through' effect. The system integrates a Force Dimension Omega. 6 master device with an EtherCAT-driven dual-axis slave mechanism and a Kunwei KWR36 6-DOF force sensor. A 7-state Markov transition model, utilizing fuzzy logic fusion of real-time probability metrics, dynamically adjusts four control weights to provide adaptive force protection and autonomous needle rotation. Experimental results in synthetic tissue phantoms demonstrate a 20% reduction in peak puncture force and significantly enhanced position tracking compared to pure bilateral teleoperation. The framework ensures statistically secure control handovers based on verified human intent.