In Minimally Invasive Robotic Surgery (MIRS),
the surgical instrument is usually inserted inside the patient’s
body through a small incision, which acts as a Remote Center
of Motion (RCM). Serial-link manipulators can be used as
macro robots on which micro surgical robotic instruments are
mounted to increase the number of degrees of freedom (DOFs)
of the system and ensure safe task and RCM motion execution.
However, the surgical instrument needs to be placed in an
appropriate configuration when completing the motion tasks.
The contribution of this work is to present a novel framework
that preoperatively identifies the best base configuration, in
terms or Roll, Pitch, and Yaw angles, of the micro surgical
instrument with respect to the macro serial-link manipulator’s
end-effector in order to achieve the maximum accuracy and
dexterity in performing specified tasks. The framework relies
on Hierarchical Quadratic Programming (HQP) for the control,
Genetic Algorithm (GA) for the optimization, and on a resilience
to error strategy to make sure deviations from the optimum do
not affect the system’s performance.
Simulation results show that the mounting configuration of
the surgical instrument significantly impacts the performance
of the whole macro-micro manipulator in executing the desired
motion tasks, and both the simulation and experimental results
demonstrate that the proposed optimization method improves the
overall performance.