  Purpose - Skullbase surgery demands exceptional precision when removing bone
in the lateral skull base. Robotic assistance can alleviate the effect of human
sensory-motor limitations. However, the stiffness and inertia of the robot can
significantly impact the surgeon's perception and control of the tool-to-tissue
interaction forces. Methods - We present a situational-aware, force control
technique aimed at regulating interaction forces during robot-assisted
skullbase drilling. The contextual interaction information derived from the
digital twin environment is used to enhance sensory perception and suppress
undesired high forces. Results - To validate our approach, we conducted initial
feasibility experiments involving a medical and two engineering students. The
experiment focused on further drilling around critical structures following
cortical mastoidectomy. The experiment results demonstrate that robotic
assistance coupled with our proposed control scheme effectively limited
undesired interaction forces when compared to robotic assistance without the
proposed force control. Conclusions - The proposed force control techniques
show promise in significantly reducing undesired interaction forces during
robot-assisted skullbase surgery. These findings contribute to the ongoing
efforts to enhance surgical precision and safety in complex procedures
involving the lateral skull base.
