Vascular intervention robot based on artificial intelligence with 0.5mm precision that can increase the accuracy of the procedure and reduce the radiation exposure of the operator and the patient by providing 2D/3D medical image data information and procedure guidance

• Development of a robot system with 0.5mm precision applicable to general vascular intervention
• Development of a biological structure simulation steering catheter
• Development of artificial intelligence based vascular interventional navigation system
• Safety proven through phantom model experiments and preclinical animal tests

Functional Requirements of the Robotic System for Sinus Surgery to approach the blind spots through the nostrils without any external incision.

• New bendable endoscopic devices
• Dual master-slave robotic system with navigation system

Endoscope holder system with AR navigation for reduction of fatigue due to endoscope holding and minimization of marker interference

• Design endoscope holder with AR navigation system

In the case of the Da Vinci System, it is difficult to use for trans-oral surgery due to the thick robotic arms. Therefore, it is necessary to design a robot that is slim and light but rigid for intraoral surgery. In addition to safely removing the tumor, it is important to minimize the morbidity and functional loss of the patient after surgery.

• Slave system design using stacked parallel mechanism with static balance structure
• Master-Slave robot control
• Surgical tool end-effector design

The developed otolaryngology surgical robot was applied to mastectomy, which is a surgical procedure to remove the area of infection of the mastectomy bone. A mastoidectomy is a common procedure for accessing the inner ear area.

• A passive robot with 4 bar stackable mechanism and counter balancing was developed.
• By using the navigation software combined with warning algorithm, it is possible to grasp the position of the target organ and surgical tool in real time during surgery, and when approaching the target organ, a warning sound is generated. In particular, when the surgical tool approaches less than a preset distance, the robot is stopped using a magnetic brake.

There are some limitations that cannot be overcome with conventional robot technologies only. We are trying to solve these limitations through artificial intelligence algorithms.

• Deep neural network for auto-balancing otologic surgery robot
• U-net based automatic segmentation and surgical navigation system for transsphenoidal pituitary surgery
• Reinforcement learning for vascular intervention robot

This research aims at developing of a new master-slave robotic system which facilitates the insertion motion of the endoscope in a safe manner and expand less power by providing the doctor with a scale-downed haptic force and moment feedback.

• A slave device grip the whole body of the endoscope just the same way as the surgeon does and perform insertion motion by the command of a master robot.
• Two-module master device is used for control the slave device. One module is used for insertion and twisting motion of the tube, the other module is used for controlling two steering motions of the endoscope tip.