A Proportional Control Method of Manipulator Movement Speed ​​Based on Myoelectricity

Abstract

The invention discloses a method for controlling the action speed ratio of a manipulator based on myoelectricity; firstly, the surface electromyography signals of the extensor carpi ulnaris and the flexor carpi radialis are collected by an electromyography acquisition instrument, and the starting point of the action is determined by an energy threshold method. The starting position and the ending position are taken as the action EMG signal, and the smoothing window average power of the signal is extracted; the original surface EMG signal is multi-scale decomposed by the wavelet analysis method, and the multi-scale fuzzy entropy feature of the signal is extracted, and the feature vector input is composed of the average power The extended K-nearest neighbor model classifier recognizes hand movements, and at the same time fits the movement speed of the operator and the manipulator through an orthogonal polynomial, and finally controls the manipulator to complete the corresponding action at the corresponding speed. The invention improves the naturalness and initiative of human-computer interaction, thereby improving the accuracy and convenience of operation, reducing the risk level of manipulator operation, and enabling the manipulator to complete relatively complicated and dangerous tasks.

Description

Technical field [0001] The invention relates to a method for proportional control of the action speed of a manipulator, in particular, to a proportional control of the action speed of a manipulator based on electromyography. Background technique [0002] Using Surface ElectromyoGram (sEMG) on the limbs of the operator to control the manipulator has the characteristics of natural movement and good bionic performance. It is an ideal control signal source for man-machine interaction systems. There are many scholars at home and abroad doing research on electromyography control. Koirala.k of the Worcester Institute of Technology in Massachusetts, USA, used EMG signals to predict the activity patterns of human motor muscle groups, and used sEMG signals to estimate the torque of prosthetic joints. Blana D of the Institute of Medical Science and Technology at Keele University in the United Kingdom designed a musculoskeletal model for amputees, using the sEMG signal obtained from the res...

AI Technical Summary

Problems solved by technology

However, when the low-order model fails to achieve the fitting effect and a high-order model needs to be established, the least squares method becomes inaccurate, and the residual sum of squares also changes exponentially with the increase of the model order

At the same time, the solution of the least squares method in the low-order model can usually meet the real-time requirements of the control, and when the matrix inversion or ill-conditioned matrix appears in the high-order model, the time complexity will be greatly increased.

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