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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 1998: Tasks and Methods in Applied Artificial Intelligence pp 115–121Cite as

A genetic algorithm for robust motion planning

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1416))

Abstract

This paper proposes a solution by genetic algorithms to the problem of planning a robust and suboptimal trajectory in the velocity space of a mobile robot. Robust trajectories are obtained introducing cumulative noise in the evaluation of the fitness function and introducing modifications in the genetic algorithm to taking into account this new feature. Results are presented that show the performance of the algorithm in different environments and the influence of the noise in the planned trajectories.

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References

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Author information

Authors and Affiliations

  1. Grupo i3a: Informática Industrial e Inteligencia Artificial Departamento de Ciencia de la Computación e Inteligencia Artificial, Universidad de Alicante, E-03080, San Vicente, Spain

    Domingo Gallardo, Otto Colomina, Francisco Flórez & Ramón Rizo

Authors
  1. Domingo Gallardo
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  2. Otto Colomina
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  3. Francisco Flórez
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  4. Ramón Rizo
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Editor information

Angel Pasqual del Pobil José Mira Moonis Ali

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© 1998 Springer-Verlag Berlin Heidelberg

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Gallardo, D., Colomina, O., Flórez, F., Rizo, R. (1998). A genetic algorithm for robust motion planning. In: Pasqual del Pobil, A., Mira, J., Ali, M. (eds) Tasks and Methods in Applied Artificial Intelligence. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64574-8_397

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  • DOI: https://doi.org/10.1007/3-540-64574-8_397

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64574-0

  • Online ISBN: 978-3-540-69350-5

  • eBook Packages: Springer Book Archive

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