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A Hybrid EDA/Nelder-Mead for Concurrent Robot Optimization

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Hybrid Intelligent Systems (HIS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 923))

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Abstract

We introduce an optimization algorithm which combines an Estimation of Distribution Algorithm (EDA) and the Nelder-Mead method for global and local optimization, respectively. The proposal not only interleaves global and local search steps but takes advantage of the information collected by the global search to use it into the local search and backwards, providing of an efficient symbiosis. The algorithm is applied to the concurrent optimization of a rehabilitation robot design, that is to say, to the dimensional synthesis as well as the determination of control gains. Finally, we present an statistical analysis and evidence about the performance of this symbiotic algorithm.

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References

  1. Abedi, M., Moghaddam, M.M., Fallah, D.: A poincare map based analysis of stroke patients walking after a rehabilitation by a robot. Math. Biosci. 299, 73–84 (2018)

    Article  MathSciNet  Google Scholar 

  2. Banala, S.K., Agrawal, S.K., Scholz, J.P.: Active leg exoskeleton (ALEX) for gait rehabilitation of motor-impaired patients. In: IEEE 10th International Conference on Rehabilitation Robotics, ICORR 2007, pp. 401–407. IEEE (2007)

    Google Scholar 

  3. Cheng, R., He, C., Jin, Y., Yao, X.: Model-based evolutionary algorithms: a short survey. Complex Intell. Syst. 4, 283–292 (2018)

    Article  Google Scholar 

  4. Efron, B., Tibshirani, R.: An Introduction to the Bootstrap. CRC Press, Boca Raton (1994)

    MATH  Google Scholar 

  5. Fong, S., Deb, S., Chaudhary, A.: A review of metaheuristics in robotics. Comput. Electr. Eng. 43(Suppl. C), 278–291 (2015). http://www.sciencedirect.com/science/article/pii/S0045790615000154

  6. Nelder, J.A., Mead, R.: A simplex method for function minimization. Comput. J. 7(4), 308–313 (1965)

    Article  MathSciNet  Google Scholar 

  7. Oña, E., Cano-de la Cuerda, R., Sánchez-Herrera, P., Balaguer, C., Jardón, A.: A review of robotics in neurorehabilitation: towards an automated process for upper limb. J. Healthcare Eng. 2018, 19 p. (2018)

    Google Scholar 

  8. Ravichandran, T., Wang, D., Heppler, G.: Simultaneous plant-controller design optimization of a two-link planar manipulator. Mechatronics 16(3), 233–242 (2006)

    Article  Google Scholar 

  9. Schmidt, H., Werner, C., Bernhardt, R., Hesse, S., Kruger, J.: Gait rehabilitation machines based on programmable footplates. J. Neuroeng. Rehabil. 4(1), 2 (2007)

    Article  Google Scholar 

  10. Valdez, S.I., Botello-Aceves, S., Becerra, H.M., Hernández, E.E.: Comparison between a concurrent and a sequential optimization methodology for serial manipulators using metaheuristics. IEEE Trans. Ind. Inform. 14(7), 3155–3165 (2018)

    Article  Google Scholar 

  11. Valdez-Peña, S.I., Hernández-Aguirre, A., Botello-Rionda, S.: Approximating the search distribution to the selection distribution in EDAs. In: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, GECCO 2009, pp. 461–468. ACM (2009). http://doi.acm.org/10.1145/1569901.1569965

  12. Yano, H., Tanaka, N., Kamibayashi, K., Saitou, H., Iwata, H.: Development of a portable gait rehabilitation system for home-visit rehabilitation. Sci. World J. 2015, 12 p. (2015)

    Google Scholar 

  13. Zavala, G., Nebro, A., Luna, F., Coello Coello, C.: A survey of multi-objective metaheuristics applied to structural optimization. Struct. Multidiscip. Optim. 49(4), 537–558 (2014)

    Article  MathSciNet  Google Scholar 

  14. Zhang, C., Lan, B., Matsuura, D., Mougenot, C., Sugahara, Y., Takeda, Y.: Kinematic design of a footplate drive mechanism using a 3-DOF parallel mechanism for walking rehabilitation device. J. Adv. Mech. Des. Syst. Manuf. 12(1), JAMDSM0017 (2018)

    Google Scholar 

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Acknowledgments

Part of this work have been supported through grants AEM-Conacyt 262887, SIP-IPN 20181422.

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Authors and Affiliations

  1. Universidad de Guanajuato, DICIS, Salamanca, Mexico

    S. Ivvan Valdez

  2. Instituto Politécnico Nacional, ESIME Ticoman, Mexico City, Mexico

    Eusebio Hernandez

  3. Tecnológico de Monterrey, Altamira, Mexico

    Sajjad Keshtkar

Authors
  1. S. Ivvan Valdez
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  2. Eusebio Hernandez
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  3. Sajjad Keshtkar
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Corresponding author

Correspondence to Eusebio Hernandez .

Editor information

Editors and Affiliations

  1. School of Engineering, Instituto Superior de Engenharia (ISEP/IPP), Porto, Portugal

    Ana Maria Madureira

  2. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  3. Machine Intelligence Research Labs, Auburn, WA, USA

    Niketa Gandhi

  4. Department of Production and Systems, University of Minho, Guimarães, Portugal

    Maria Leonilde Varela

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Valdez, S.I., Hernandez, E., Keshtkar, S. (2020). A Hybrid EDA/Nelder-Mead for Concurrent Robot Optimization. In: Madureira, A., Abraham, A., Gandhi, N., Varela, M. (eds) Hybrid Intelligent Systems. HIS 2018. Advances in Intelligent Systems and Computing, vol 923. Springer, Cham. https://doi.org/10.1007/978-3-030-14347-3_20

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