This master thesis presents the design and evaluation of MR-safe 3D-printable force sensors for MRI-guided robotic systems. Current systems rely solely on imaging feedback and lack direct force sensing at the needle tip, resulting in inaccurate and slow positioning.
To address this, two sensing principles are developed and compared. The ATLAS method estimates force by measuring the displacement of 3D-printed springs. The AEOLUS method estimates force by modulating pneumatic airflow within a 3D-printed air chamber. Together, they demonstrate that MR-safe force sensing can be achieved through fundamentally different physical principles, each with distinct trade-offs in complexity, sensitivity, and integration potential.
The results demonstrate the feasibility of accessible, modular force sensing within MRI-guided systems and provide a concrete framework for integrating and tailoring these sensors to specific MR-safe applications.