Research On SEMG-based Estimation Of Arm Stiffnesss Impedance Control

In recent years,the development of robot technology is more mature,and its application field is more and more extensive.The cooperation between doctors and surgical robots has always been a research hotspot in this field.The working environment of the surgical robot is complex,which brings a lot of pressure to the docotor during the operation.This problem caused the doctor to misoperate.How to avoid misoperation effectively is still a huge challenge.The human arm is the key to human-computer interaction.The unique stiffness and motion mechanics of the human body enable it to move flexibly in complex environments and maintain high robustness.Surface electromyography(sEMG)contains rich human kinematics information and is an important carrier to explore the stiffness characteristics of the human body.Based on EMG signals,this paper studies the estimation method of human arm stiffness and the impedance control based on arm stiffness.First of all,this paper analyzes the problems of human body stiffness estimation at present.By studying the co-operation between different muscle groups on the arm and analyzing its influence on the end stiffness,to determine the position of the muscle group in which the sEMG signal is collected.The sEMG signal contains stiffness-related information,and the sEMG signal is processed according to the physiological background of the signal.The processed sEMG is highly related to the arm stiffness and muscle torque.The stiffness identification experiments are carried out.The end moment of the mechanical arm and the envelope amplitude of the sEMG signal are fitted by the least square method,and the end stiffness mapping matrix is extracted and the end stiffness of the arm is calculated.Secondly,the muscle activation is calculated by dynamic activation characteristics in the musculoskeletal model.The muscle force of human arm during exercise is calculated by the dynamic contraction characteristics in the musculoskeletal model.Through the tendon method,the muscle force arm is calculated.There is a cooperative contraction between muscles,and the muscle torque and end stiffness are fitted to the stiffness trend index of the arm joint.The feasibility of the musculoskeletal model is verified by dragging a single joint manipulator,which provides stiffness parameters for subsequent impedance control based on EMG signal stiffness estimation.Finally,two impedance control methods are realized,which are position-based impedance control and sEMG-based impedance control of human arm stiffness estimation.Under the MATLAB Simulink platform,the simulation analysis of the position-based joint impedance control method is established.The anti-jamming impedance control strategy based on sEMG is designed and simulated.The drag experiments of the operating arm under two different impedance control modes are completed on the existing operating arm experimental platform in the laboratory,and the changes of joint position and position error are analyzed,and the joint torque and joint terminal torque sensors are compared.The results show that the impedance control based on sEMG stiffness estimation can flexibly adjust the joint torque according to the specific environment of surgical drag,which is helpful for doctors to overcome the misoperation in the process of dragging surgical robot.