Artificial neural network for solving the inverse kinematic model of a spatial and planar variable curvature continuum robot

• Autorzy: Ghoul Abdelhamid , Kara Kamel , Djeffal Selman , Benrabah Mahomed , Hadjili Mohamed Laid

Identyfikatory

DOI

10.24425/ame.2022.141518

• Języki publikacji: EN

Abstrakty

EN

In this paper, neural networks are presented to solve the inverse kinematic models of continuum robots. Firstly, the forward kinematic models are calculated for variable curvature continuum robots. Then, the forward kinematic models are implemented in the neural networks which present the position of the continuum robot’s end effector. After that, the inverse kinematic models are solved through neural networks without setting up any constraints. In the same context, to validate the utility of the developed neural networks, various types of trajectories are proposed to be followed by continuum robots. It is found that the developed neural networks are powerful tool to deal with the high complexity of the non-linear equations, in particular when it comes to solving the inverse kinematics model of variable curvature continuum robots. To have a closer look at the efficiency of the developed neural network models during the follow up of the proposed trajectories, 3D simulation examples through Matlab have been carried out with different configurations. It is noteworthy to say that the developed models are a needed tool for real time application since it does not depend on the complexity of the continuum robots' inverse kinematic models.

Słowa kluczowe

EN

continuum robots; inverse kinematic model; artificial neural network

PL

roboty kontinuum; odwrotny model kinematyczny; sztuczna sieć neuronowa

• Wydawca: Komitet Budowy Maszyn PAN
• Czasopismo: Archive of Mechanical Engineering
• Rocznik: 2022
• Tom: LXIX, nr 4
• Strony: 595--613
• Opis fizyczny: Bibliogr. 31 poz., rys., tab.

Twórcy

autor

Ghoul Abdelhamid

• Université of Blida 1, Laboratoire des systèmes électriques et télécommande, Faculty of Technology, Blida, Algeria

autor

Kara Kamel

• Université of Blida 1, Laboratoire des systèmes électriques et télécommande, Faculty of Technology, Blida, Algeria

autor

Djeffal Selman

• University of Larbi Ben M’hidi, Faculty of Science and Applied Sciences, Oum El Bouaghi, Algeria

autor

Benrabah Mahomed

• University of Sciences and Technology Houari Boumediene, Laboratoire des systèmes électriques et télécommande, Faculty of Electrical Engineering, Algiers, Algeria

autor

Hadjili Mohamed Laid

• Haute Ecole Bruxelles, Ecole Supérieure d’Informatique, Brussels, Belgium

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).