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A sensorless haptic interface for robotic minimally invasive surgery
Robotic minimally invasive surgery (R-MIS) has gained in popularity due to its advantages of improving the accuracy and dexterity of surgical interventions while minimizing trauma to the patient. However, because of the loss of direct contact with the surgical site, the surgeon cannot perceive tactile information, which may adversely affect surgical efficiency and/or efficacy. The lack of haptic feedback is regarded as a limiting factor in existing R-MIS technology. To solve this problem, researchers have incorporated force sensors on the surgical tools to measure the tool-tissue interaction forces, and reproduce these forces at the surgeon console. However, the employment of force sensors leads to other problems limiting their practical application. For example, they may require many extra system components and manufacturing steps which likely affect the economy and robustness of the surgical devices, and they may also have sterilization problems. This thesis explores the feasibility of utilizing driving motors’ current to sensorlessly estimate the tool-tissue interaction forces for a 3-DOF motorized surgical grasper. A mechanism based on planetary gear theory has been applied to decouple the motions and forces in grasp, pitch and yaw, and then the sensorless force estimation method is applied on these three DOFs separately. A series of different prototypes have been used to validate scenarios approaching the conditions of real surgical applications. Finally, a 3-DOF low-inertia master robot with haptic features was fabricated to control the surgical grasper and reflect the tool-tissue interaction forces to the surgeon’s hand. With the haptic system, test subjects can successfully distinguish the stiffness of wood, foam and sponge using all three DOFs; and the location of a simulated tumor embedded in tissue can be clearly identified. The experiment also demonstrates that haptic feedback can help surgeons regain the tactile information and help them to explore the mechanical properties of tissue; this real-time force feedback may enable surgeons to decrease operation forces and avoid tissue damage.
Zhao, Baoliang, "A sensorless haptic interface for robotic minimally invasive surgery" (2015). ETD collection for University of Nebraska - Lincoln. AAI3718071.