Research On Control Of Mechanical Arm Force In Laparoscopic Surgery Based On Admittance Model

In order to fundamentally solve the shortcomings of laparoscopic minimally invasive surgery,break through the limits of minimally invasive surgery and improve the quality of surgery,the technology of laparoscopic surgery robots combined with robotics has become a research hotspot in the field of medical robotics.To this end,this dissertation has carried out related research on the manipulator of the laparoscopic surgery robot,which mainly involves the motion calibration based on the measurement configuration and the force pendulum control of the manipulator.First,so as to obtain accurate kinematics geometric parameters of the manipulator,and then obtain accurate force transfor mation matrix and speed Jacobian matrix,a kinematic calibration study based on measurement configuration selection has been carried out for force positioning manipulator.Analysis of the mechanical arm of preoperative beam position and the function of dou ble parallelogram mechanism,based on the D-H method is modified to the phenomenon that the singularity in parallel to the adjacent joints mechanical arm is inverse kinematics model is established,using Matlab simulation results verify the accuracy of inverse kinematics,on this basis,the kinematic error model is established and the simulation verifies the correctness.The preoperative positioning of the manipulator and the function of the double parallelogram mechanism are analyzed.Based on the improved D-H parameter method,the forward and inverse kinematics model of the manipulator with singular phenomena in adjacent parallel joints is established,and the forward and inverse kinematics models are verified by Matlab simulation.The correctness of kinematics,on this basis,a kinematic error model is established and the correctness is verified by simulation.Secondly,for the sake of realizing the force positioning control of the manipulator during the operation,and obtaining a compliant and natural way of adjusting the posture of the manipulator for laparoscopic surgery,a variable damping force positioning model based on reinforcement learning is proposed.Based on the admittance model,the force positioning control principle and the influence of the admittance parameters on the speed response are analyzed,and the gravity compensation model of the six-dimensional force signal input in the force positioning control is established,and the online identification of the robot force positioning based on the multithreaded A3 C algorithm is proposed.The damping parameter adjustment model in sports uses a multi-threaded training mechanism for training and uses the difference weight update between the action state value and the estimated mean value to avoid the positive trap.The simulation analyzes its advantage with the variable parameter DDPG algorithm in the convergence index.Finally,an experimental platform for a laparoscopic surgical robot has been built,and a motion calibration experiment based on measu rement configuration selection is carried out on the slave robot arm using the dynamic tracking system,which verifies the feasibility of the proposed observability index and the performance of the particle swarm search algorithm.With the improvement of convergence speed and accuracy,the end pose accuracy of the platform is obtained and compensated,and accurate kinematic geometric parameters are obtained.An accurate gravity compensation model based on the force transformation matrix and an accurate grav ity compensation model based on the velocity Jacobian matrix is obtained.The end speed lays the foundation for force setting control.To verify the compliant effect of the multithreaded A3 C algorithm in the force positioning motion of the manipulator,through comparison with the fixed low and high damping force positioning experiments,it is obtained that the trajectory and speed tracking errors are reduced significantly,respectively,which proves that the multithreaded A3 C algorithm can be better in realizing the position control of compliance force.