Research On Grip Force Sensing And Feedback Control Of Surgical Robot

Force perception plays an important role in minimally invasive surgery assisted with surgery robot,which can improve the safety and transparency of the operation and give the doctor a better sense of surgical immersion.However,since the surgical instruments at the end of the surgical robot need to contact human tissue,so it has a very high cleanliness requirement.It is difficult to integrate the force sensor on the device,so the force perception is not well applied to the surgical robot.In response to this problem,this paper will study the surgical robots with grip force detection and force feedback.Firstly,the kinematics modeling of the surgical robot is carried out.Due to the special steel wire transmission structure of the surgical instruments from the end of the hand,the change of the posture of the surgical robot will also affect the end grip force.Firstly,the grip force is analyzed from the hand movement.Then,according to the requirements of real-time and other requirements,the method of quickly obtain the inverse solution is designed to solve the problem that the traditional Jacques matrix is slow in the problem of inverse solution.Secondly,the method of detecting the grip force of the surgical instruments from the end of the hand is studied,and a sensorless grip force detection scheme is designed.The scheme mainly uses the neural network optimized by genetic algorithm to learn the model between the motor output signal and the grip force.According to the obtained model,the grip force can be estimated online according to the current motor output signal during the operation.In order to illustrate the accuracy of the sensorless detection method,the sensorless grip force detection method and the sensor-based grip force detection method are compared and analyzed.The sensorless grip force detection method has higher accuracy and is has not the hysteresis problem of the sensor detection method.It is simpler,more effective,and lower in cost.Thirdly,the research on the grip force feedback control is carried out.Firstly,the dynamic interference introduced by the human power in the force feedback control system is analyzed by establishing the model of human hand and master robot.The fuzzy PID is designed as a closed-loop force controller of the grip force feedback control system,which have human hand dynamic interference and uncertain impedance model.Then the simulation is done to verify the response of the controller.The force feedback control method of the verification design can quickly and accurately feedback the grip force.Finally,the verification platform of relevant research content is built.Firstly,the practicality of the method of designing the fast analytical solution is verified by comparing the relative displacements of the master robot and the slave robot.Then the scheme of sensorless grip force detection which is simpler and more effective is verified.The detection scheme is verified.Comparing the true grip force detected by the Flexiforce sensor,it can be verified that the design of the grip force detection scheme can meet the detection requirements.Finally,the overall experiment of grip force detection and the force feedback is carried out.By comparing the feedback force and the detected grip force,it is verified that the designed fuzzy PID force controller has practical application value.Verify that the fuzzy PID force controller studied in this paper has the advantages of fast response and high accuracy.