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Forward Kinematic Modeling of Conical-Shaped Continuum Manipulators

Published online by Cambridge University Press:  03 February 2021

A. H. Bouyom Boutchouang Open the ORCID record for A. H. Bouyom Boutchouang [Opens in a new window] ,
Achille Melingui ,
J. J. B. Mvogo Ahanda Open the ORCID record for J. J. B. Mvogo Ahanda [Opens in a new window] ,
Othman Lakhal ,
Frederic Biya Motto  and
Rochdi Merzouki
A. H. Bouyom Boutchouang*
Affiliation:
Department of Electrical and Telecommunications Engineering, Ecole Nationale Supérieure Polytechnique, University of Yaounde I, Yaounde 8390, Cameroon. E-mail: [email protected]
Achille Melingui
Affiliation:
Department of Electrical and Telecommunications Engineering, Ecole Nationale Supérieure Polytechnique, University of Yaounde I, Yaounde 8390, Cameroon. E-mail: [email protected]
J. J. B. Mvogo Ahanda
Affiliation:
Department of Electrical and Power Engineering, University of Bamenda, Bamenda 39 Bambili, Cameroun. E-mail: [email protected]
Othman Lakhal
Affiliation:
CRIStAL Laboratory, CNRS-UMR,Villeneuve d’Ascq 59655, France. E-mails: [email protected], [email protected]
Frederic Biya Motto
Affiliation:
Department of Physic’s, Faculty of Sciences, University of Yaounde I, Yaounde 8390, Cameroon. E-mail: [email protected]
Rochdi Merzouki
Affiliation:
CRIStAL Laboratory, CNRS-UMR,Villeneuve d’Ascq 59655, France. E-mails: [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

Forward kinematics is essential in robot control. Its resolution remains a challenge for continuum manipulators because of their inherent flexibility. Learning-based approaches allow obtaining accurate models. However, they suffer from the explosion of the learning database that wears down the manipulator during data collection. This paper proposes an approach that combines the model and learning-based approaches. The learning database is derived from analytical equations to prevent the robot from operating for long periods. The database obtained is handled using Deep Neural Networks (DNNs). The Compact Bionic Handling robot serves as an experimental platform. The comparison with existing approaches gives satisfaction.

Keywords

Continuum manipulatorsForward kinematicsDeep learningAutoencoders (AE) and MLP
Type
Article
Information
Robotica , Volume 39 , Issue 10 , October 2021 , pp. 1760 - 1778
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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