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Cartesian space consensus of heterogeneous and uncertain Euler-Lagrange systems using artificial neural networks

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  • Intelligent Control and Applications
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Abstract

This work reports a radial basis Artificial Neural Network controller that solves the leader-follower and leaderless pose (position and orientation) consensus problems, in the Special Euclidean space of dimension three (SE(3)), in robot networks composed of heterogeneous (kinematically and dynamically different) and uncertain robots. The proposed approach employs, the singularity-free, unit-quaternions to represent the orientation of the end-effectors in the SE(3). The performance of the proposed controller is illustrated via simulations with a five heterogeneous robot network.

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Authors and Affiliations

  1. Department of Computer Science, CUCEI, University of Guadalajara, Guadalajara, Jalisco, Mexico

    Remberto Machuca, Carlos I. Aldana, Rodrigo Munguía & Emmanuel Nuño

Authors
  1. Remberto Machuca
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  2. Carlos I. Aldana
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  3. Rodrigo Munguía
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  4. Emmanuel Nuño
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Corresponding author

Correspondence to Emmanuel Nuño.

Additional information

Recommended by Associate Editor DaeEun Kim under the direction of Editor Myp Taeg Lim. The first and second authors thank the Mexican CONACyT for the Ms.C. grant 295996 and the Repatriación grant 262724, respectively. This work has been partially supported by the Spanish MINECO projects DPI2013-40882-P, DPI2014-57757-R and DPI2016-80077-R.

Remberto Machuca was born in Guadalajara, México, in 1985. He obtained his B.Sc. degreee in Biomedical Engineering from the University of Guadalajara, in Guadalajara, Mexico, in 2012. Currently, he is enrolled in the Department of Computer Science at the University of Guadalajara to obtain the M. Sc. degree in Electronic Engineering and Computer Science. His research interests include artificial neural networks, teleoperation and consensus of multiple Euler- Lagrange systems. Other interests include robotics, prosthetics, and nanomaterials; areas in which he has indexed scientific journal publications.

Rodrigo Munguía was born in Guadalajara, México. He received the Ph.D. degree in Electrical Engineering (2009) and the M.S. degree in computer science (2006) from the Technical University of Catalonia (UPC), Spain. He received the B.Eng. degree in engineering from the University of Guadalajara, Guadalajara, Mexico. Since the 2010, he is a titular professor with the Department of Computer Science of the University of Guadalajara. His research interests include mobile robotics, navigation systems for autonomous vehicles, automatic control, optimal state estimation and computer vision.

Carlos I. Aldana received the B.Sc. degree in communications and electronic engineering from the University of Guadalajara in 2002, M.Sc. degree in Automatic Control from the CINVESTAV-IPN in 2004 and the Ph.D. degree in Automatic Control, Robotics and Computer Vision from the Technical University of Catalonia, Spain, in 2015. He worked for three years as software testing engineer at Siemens VDO and Continental Automotive at the development department in Guadalajara, Mexico. Actually he is a professor of the Department of Computer Science of the University of Guadalajara. His current research interests include task space control of robot manipulators, control of robot networks, teleoperation and model predictive control.

Emmanuel Nuño was born in Guadalajara, México, in 1980. He obtained his B.Sc. in Communications and Electronics Engineering from the University of Guadalajara in 2002. He received the Ph.D. degree in Advanced Automation and Robotics from the Technical University of Catalonia, Spain, in July 2008. He has held different research internships at the Laboratoire des Signaux et Systemes, SUPELEC, at the Coordinated Science Laboratory at University of Illinois, Urbana- Champaign, at the Institute of Industrial and Control Engineering at the Technical University of Catalonia and at the Engineering Faculty of the National Autonomous University of Mexico. Since 2008 he is a Titular Professor in the Department of Computer Science of the University of Guadalajara.

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Machuca, R., Aldana, C.I., Munguía, R. et al. Cartesian space consensus of heterogeneous and uncertain Euler-Lagrange systems using artificial neural networks. Int. J. Control Autom. Syst. 15, 1447–1455 (2017). https://doi.org/10.1007/s12555-015-0361-z

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  • DOI: https://doi.org/10.1007/s12555-015-0361-z

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