Developing application techniques of kinematics and simulation model for InMoov robot

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.261039

Keywords:

InMoov robot, manipulator kinematics, iterative algorithm, python mean square error

Abstract

In this work, the direct and inverse kinematic analysis of both robot arms are investigated based on the analytical and informational representation. The results of the study will be used to provide the functionality of gesturing by a robot in sign language, both Kazakh and other languages, used in educational systems, especially in children's institutions and societies for deaf people. A simulation model of the movement of the robot's arms in the workspace has been studied and built. The developed model will be further implemented and used as mathematical and information support for the created robot. The developed library contains implementations of forward kinematics and iterative algorithms for inverse kinematics.

The InMoov robot is a platform widely used in research tasks, supported by the MyRobotLab package. A direct kinematic model for the left and right hands of the robot has been studied. Based on the Python programming language, the working space for robot manipulators was calculated, using the matpilotlib library, an iteration method algorithm was developed to find the probable path of robot manipulators in space. A model of a structured artificial neural network (ANN) is proposed, which is used to find a solution to the inverse kinematics of the InMoov robot with six degrees of freedom (4-dof). The applied ANN model is a multilayer perceptron neural network (MLPNN) in which the learning rule of the Adam-a gradient diskend type is applied. To solve this problem, the problem of finding the best ANN configuration was studied. It has been established that a multilayer parseptron neural network gives the minimum mean square error. The regression coefficient analysis, which shows a 95.6 % fit of all communication variables, is acceptable for obtaining the inverse kinematics of the InMoov robot.

Author Biographies

Chingis Kenshimov, Institute of Information and Computational Technologies

PhD, Associate Professor, Leading Researcher

Laboratory of Artificial Intelligence and Robotics

Talgat Sundetov, Institute of Information and Computational Technologies

Doctoral Student, Researcher

Laboratory of Artificial Intelligence and Robotics

Murat Kunelbayev, Institute of Information and Computational Technologies

Research Associate

Laboratory of Artificial Intelligence and Robotics

Magzhan Sarzhan, Institute of Information and Computational Technologies

Doctoral Student, Researcher

Laboratory of Artificial Intelligence and Robotics

Madina Kutubayeva, L. N. Gumilyov Eurasian National University

Doctoral Student Computer Science and Software

Arman Amandykuly, Institute of Information and Computational Technologies

Student, Researcher

Laboratory of Artificial Intelligence and Robotics

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Published

2022-08-30

How to Cite

Kenshimov, C., Sundetov, T., Kunelbayev, M., Sarzhan, M., Kutubayeva, M., & Amandykuly, A. (2022). Developing application techniques of kinematics and simulation model for InMoov robot. Eastern-European Journal of Enterprise Technologies, 4(7 (118), 79–88. https://doi.org/10.15587/1729-4061.2022.261039

Issue

Vol. 4 No. 7 (118) (2022): Applied mechanics

Section

Applied mechanics

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Copyright (c) 2022 Chingis Kenshimov, Talgat Sundetov, Murat Kunelbayev, Magzhan Sarzhan, Madina Kutubayeva, Arman Amandykuly

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