This paper presents a control strategy that secures both precision and manipulation sensitivity of remote center motion with direct teaching for a surgical assistant robot. Remote center motion is an essential function of conventional laparoscopic surgery, and the most intuitive way a surgeon manipulates a robot is through direct teaching. The surgical assistant robot must maintain the position of the insertion port in three-dimensional space during the four-degree-of-freedom motions such as pan, tilt, spin, and forward/backward. In addition, the robot should move smoothly when controlling it with the hands during the surgery. In this study, a six-degree-of-freedom collaborative robot performs the cone-shaped trajectory with pan and tilt motion of an end-effector keeping the position of the remote center. Instead of the bulky mechanically constrained remote center motion mechanism, a conventional collaborative robot is used to mimic the wrist movement of a scrub nurse. A force/torque sensor that is attached between the robot and end-effector estimates the surgeon’s intention. A direct teaching control strategy based on position control is applied to guarantee precise remote center position maintenance performance. A motion generation algorithm is designed to generate motion by utilizing a force/torque sensor value. The parameters of the motion generation algorithm are optimized so that the robot can be operated with uniform sensitivity in all directions. The precision of remote center motion and the torque required for direct teaching are analyzed through pan and tilt motion experiments.

This paper shows the design and modeling of an end effector with a bidirectional telescopic mechanism to allow a surgical assistant robot to hold and handle surgical instruments. It also presents a force-free control algorithm for the direct teaching of end effectors. The bidirectional telescopic mechanism can actively transmit force both upwards and downwards by staggering the wires on both sides. In order to estimate and control torque via motor current without a force/torque sensor, the gravity model and friction model of the device are derived through repeated experiments. The LuGre model is applied to the friction model, and the static and dynamic parameters are obtained using a curve fitting function and a genetic algorithm. Direct teaching control is designed using a force-free control algorithm that compensates for the estimated torque from the motor current for gravity and friction, and then converts it into a position control input. Direct teaching operation sensitivity is verified through hand-guiding experiments.