Background: Neurosurgery demands high precision, and robotic‐assisted systems are increasingly employed to enhance surgical outcomes. This study focuses on a hybrid robotic‐assisted system for neurosurgery, addressing forward and inverse kinematics, Jacobian matrices, and system singularities.
Methods: The system is simulated using MATLAB/Simscape Multibody to achieve accurate kinematic and dynamic representations. An inverse kinematics framework was developed for generating and validating a circular trajectory at the end‐ effector tip. Two control strategies are compared: traditional active joint PID control and combined trajectory feedback plus feedforward control.
Results: The combined control strategy significantly improves performance, reducing the maximum absolute error of each output by an average of 46.5% and the mean square error by 50.31% under optimal conditions.
Conclusion: The findings highlight the potential of trajectory feedback and feedforward control to enhance the precision and reliability of robotic‐assisted neurosurgical procedures.