Research On Grinding Path And Compliance Control Of A Spinal Surgical Robot For Lamina Grinding

Laminectomy is a common spinal operation.Doctors hold a grinding drill to remove the lamina of the diseased area in order to release the pressure of the spinal cord.Lamina grinding is one of the key operations,but manual grinding is time-consuming,difficult and high risk,which has high requirements for doctors’ experience and physical strength.The development of robot assisted surgery technology provides a new way for lamina grinding.Compared with the traditional doctor operation,the robot has the advantages of high positioning accuracy,stable operation and immune to radiation.After computer enhanced processing and modeling,the CT medical images used by the robot can provide accurate surgical path planning for the robot and eliminate the risk of being misled by experience in manual analysis.In addition,in order to ensure the ability of surgical robot to interact with complex environment,it needs to have a certain degree of flexibility.In this paper,the path planning of robot grinding based on medical image,robot compliance force control including preoperative positioning and intraoperative autonomous grinding are studied,and the experimental verification of each scheme is carried out.Firstly,on the basis of the structural characteristics of the existing spinal surgery robot,the kinematics model is established,and the velocity Jacobian matrix is further derived,which provides the mathematical model basis for the follow-up force /position control,and the correctness of the kinematics is verified by CO simulation.After kinematic calibration,the positioning accuracy and repeated positioning accuracy of the robot are measured by using laser tracker,and the driving force sensors of each joint of the robot are analyzed and tested to ensure that the motion accuracy and force sensing ability of the robot meet the requirements of subsequent research.Secondly,a path planning method of laminectomy based on 3D reconstruction of medical images is proposed.The level set method is used to extract the surgical region from the original image to remove the background interference.The 3D reconstruction algorithm based on moving cube is used to complete the 3D reconstruction of spine for 3D space oriented planning.Finally,the grinding path planning is realized by sampling the surface of the lamina model through the interactive boundary frame,supplemented by the middle layer sampling.In order to ensure that the surgical robot can adapt to the complex working environment,it needs to have flexibility,mainly including preoperative positioning and intraoperative autonomous grinding function.The characteristics of the surgical robot are analyzed,and the appropriate overall force control scheme is determined.For preoperative zero force drag,a mobility model based on velocity adjustment is established for motion control,and the force sensor is compensated by gravity.According to the motion state of the robot,the operator’s intention is estimated,and the admittance parameters are adjusted online by fuzzy control to achieve more flexible drag control.For the control of grinding force,the grinding process is analyzed,and the scheme of controlling the movement of the cutter in two directions is determined.The adaptability of the fuzzy controller is improved by the double-layer structure,and the grinding force is stabilized in a reasonable range by adjusting the grinding parameters in real time.Finally,the built of the surgical robot experimental platform are completed.The control algorithm of bone grinding force is simulated to verify its feasibility.The algorithms of zero force drag control and grinding force control are programmed and tested.Comparing the interaction force and speed of dragging process controlled by constant parameter and variable parameter admittance,the effectiveness of fuzzy variable parameter control algorithm is illustrated.Compared with position control,single-layer fuzzy force control and double-layer fuzzy force control,the rationality of grinding force control algorithm is verified.Laminectomy is a common spinal operation,in which the doctor holds a grinding drill to remove the lamina of the diseased part of the patient,so as to release the pressure of the spinal cord.Lamina grinding is one of the key operations,which is time-consuming,difficult and highly risky.It has high requirements for doctors’ experience and physical strength.However,the development of robot assisted surgery technology provides a new way for lamina grinding.Compared with the traditional doctor operation,the robot has the advantages of high positioning accuracy,stable operation and immune to radiation.After computer enhanced processing and modeling,the CT medical images used by the robot can provide accurate surgical path planning for the robot and eliminate the risk of being misled by experience in manual analysis.In addition,in order to ensure the ability of surgical robot to interact with complex environment,it needs to possess flexibility.In this paper,the path planning of robot grinding based on medical image,robot compliance force control including preoperative positioning and intraoperative active grinding are studied,and each scheme is verified by experiments.