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Trajectory planning for a manipulator with nonlinear Coulomb friction using a dynamically incremental genetic algorithm

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Abstract

Global warming and environmental destruction are caused in part by the mass consumption of energy by industries that use robotic manipulators. Hence, there is a need to minimize the energy used for manipulator control systems. It is relatively easy to analytically obtain an optimal solution for a linear system. However, a multi-link manipulator is governed by a nonlinear dynamical equation that is difficult to solve as a two-point boundary value problem. Here, the manipulator angles are approximated by Taylor and Fourier series, whose coefficients are sought by a genetic algorithm (GA) to optimize the objective function subject to the boundary conditions. A search method is proposed for planning the trajectory of a manipulator with nonlinear friction and geometrical constraints.

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Authors and Affiliations

  1. Department of Electrical Engineering and Information Science, Kure College of Technology, 2-2-11 Agaminami, Kure, Hiroshima, 737-8506, Japan

    Yoshio Yokose

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  1. Yoshio Yokose
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Correspondence to Yoshio Yokose.

Additional information

This work was presented in part at the 21st International Symposium on Artificial Life and Robotics, Beppu, Oita, January 20–22, 2016.

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Cite this article

Yokose, Y. Trajectory planning for a manipulator with nonlinear Coulomb friction using a dynamically incremental genetic algorithm. Artif Life Robotics 22, 31–35 (2017). https://doi.org/10.1007/s10015-016-0318-1

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  • DOI: https://doi.org/10.1007/s10015-016-0318-1

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