Study On Man-machine Interaction Of Redundant Degree Of Mechanical Arm

With the rapid development of industrial automation,the application of the manipulator in the production and everyday life has spread throughout the aerospace,industrial production,medical treatment,life service and other industries,greatly liberating the labor force,and significantly improving the quality of life of people.However,with the rapid rise of artificial intelligence technology,the manipulator has slowly failed to meet the needs of the producers through a fixed mode of manipulators under the traditional sense of equipment,so the researchers are eager to develop a man-machine interaction arm.In this paper,the technology of human-machine interaction is deeply researched based on the autonomous redundant robot platform.In order to make a more thorough understanding of the manipulator,the main design parameters and the selection of main controls are introduced in this thesis.Then we use D-H parameter method to establish its kinematics model,analyze the forward and inverse kinematics solution,and simulate the experiment to verify its accuracy.The core of human-machine interaction is how the machine understands the instructions sent by the operator to the machine and the corresponding feedback.,Fuzzy control algorithm is a kind of computer digital control technology based on fuzzy set theory,fuzzy language variable and fuzzy logic reasoning.It has a good application in the field of robot control.For the input of fuzzy control,this paper first establishes a model of the no-load attitude moment of the manipulator,realizes the model of real time no-load torque derived from real time attitude,then establishes the relationship between the change of joint current and the change of torque,and finally obtains the relationship between the real time current and the external torque.The real-time change of the manipulator's joint current is taken as input to achieve the fuzzy control of machine interaction,and the fuzzy control algorithm is verified and analyzed.In order to optimize fuzzy control algorithm,we achieve better man-machine interaction control effect.With the introduction of dynamic factors,the kinematics of the manipulator is analyzed first,then the flexible joint dynamics of the manipulator is modeled and the dynamic equation is established by combining the flexible characteristics of the manipulator's joint.Then the model parameters are introduced into the fuzzy control algorithm to optimize the control strategy.Finally,in the experimental part,the effect of the fuzzy control algorithm and the accuracy of the model are verified by the real-time interaction with the manipulator and the real-time feedback data.The results of the fuzzy control algorithm before and after the optimization are compared,and the results are obtained from the data and the experimental results respectively.After that,the model is more applicable and human-machine interaction experience is more friendly.