This paper deals with a strategy of gain optimization for the kinematic control algorithm of a wire-driven surgical robot. The proposed controller consists of the closed-loop inverse kinematics with the back-calculation method. The closed-loop inverse kinematics has 18 PID control gains, and the back-calculation method has 6 gains. An efficient strategy is designed to optimize 18 values first and then the remaining 6 values. The optimal gain sets are searched under the step input with performance indices. In this gain optimization, the objective function is defined as the minimum value of signal-to-noise ratio of the performance indices for 6 DoF (Degree-of-Freedom) motion that is based on the Taguchi method, and the constraints are applied to obtain stable responses for each motion evenly. The gain sets obtained are verified by simulations using the test trajectories. In comparative results, the optimal gain value based on the performance index combined with ISE (integral of square error) and settling time showed the best control performance.

This paper proposes a low-cost robotic surgery system composed of a general purpose robotic arm, an interface for daVinci surgical robot tools and a modular haptic controller utilizing smart actuators. The 7 degree of freedom (DOF) haptic controller is suspended in the air using the gravity compensation, and the 3D position and orientation of the controller endpoint is calculated from the joint readings and the forward kinematics of the haptic controller. Then the joint angles for a general purpose robotic arm is calculated using the analytic inverse kinematics so that that the tooltip reaches the target position through a small incision. Finally, the surgical tool wrist joints angles are calculated to make the tooltip correctly face the desired orientation. The suggested system is implemented and validated using the physical UR5e robotic arm.