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Dexterity control of multi-arm sorting robot based on machine learning

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  • Linyan Pan

Abstract

In order to overcome the problems of large dexterity control error of manipulator joint and poor sorting and positioning accuracy, this paper designs a dexterity control method of multi manipulator sorting robot based on machine learning. Firstly, the attitude of the multi manipulator coordinate system on the rigid body is obtained. Secondly, the translation matrix is constructed by using the translation transformation method. Then, the rotation matrix is constructed to determine the inverse motion law of the robot. Finally, determine the dexterity parameters of the manipulator joint, introduce the machine learning algorithm to calculate the dexterity parameter control error, and correct the error through the activation function to complete the dexterity control. The experimental results show that the error of this method is always less than 0.1% and the positioning accuracy is higher than 90%, which shows that the dexterity control effect of this method is good.

Suggested Citation

  • Linyan Pan, 2024. "Dexterity control of multi-arm sorting robot based on machine learning," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 38(1), pages 81-94.
    • Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:81-94
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