International Journal of Control, Automation and Systems 2017; 15(3): 1447-1455
Published online March 30, 2017
https://doi.org/10.1007/s12555-015-0361-z
© The International Journal of Control, Automation, and Systems
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."
Keywords Adaptive control, artificial neural networks, cartesian space, consensus, Euler-Lagrange systems.
International Journal of Control, Automation and Systems 2017; 15(3): 1447-1455
Published online June 1, 2017 https://doi.org/10.1007/s12555-015-0361-z
Copyright © The International Journal of Control, Automation, and Systems.
Remberto Machuca, Carlos I. Aldana, Rodrigo Munguía and Emmanuel Nuño*
University of Guadalajara
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."
Keywords: Adaptive control, artificial neural networks, cartesian space, consensus, Euler-Lagrange systems.
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