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GPU Accelerated Membrane Evolutionary Artificial Potential Field for Mobile Robot Path Planning

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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 940))

Abstract

This work presents a graphics processing unit (GPU) accelerated membrane evolutionary artificial potential field (MemEAPF) algorithm implementation for mobile robot path planning. Three different implementations are compared to show the performance, effectiveness, and efficiency of the MemEAPF algorithm. Simulation results for the three different implementations of the MemEAPF algorithm, a sequential implementation on CPU, a parallel implementation on CPU using the open multi-processing (OpenMP) application programming interface, and the parallel implementation on GPU using the compute unified device architecture (CUDA) are provided to validate the comparative and analysis. Based on the obtained results, we can conclude that the GPU implementation is a powerful way to accelerate the MemEAPF algorithm because the path planning problem in this work has been stated as a data-parallel problem.

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Acknowledgments

This work was supported by the Coordinación de Investigación of CETYS Universidad, and by the Mexico’s National Council of Science and Technology (CONACYT).

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Authors and Affiliations

  1. CETYS Universidad, Centro de Innovación y Diseño (CEID), Av. CETYS Universidad. No. 4., Fracc, 22210, El Lago, Tijuana, Baja California, Mexico

    Ulises Orozco-Rosas & Kenia Picos

  2. Instituto Politécnico Nacional, CITEDI-IPN, Av. Instituto Politécnico Nacional No. 1310, 22435, Nueva Tijuana, Tijuana, Baja California, Mexico

    Oscar Montiel

  3. Tecnológico Nacional de México, Calzada Del Tecnológico S/N, Tomas Aquino, 22414, Tijuana, Baja California, Mexico

    Oscar Castillo

Authors
  1. Ulises Orozco-Rosas
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  2. Kenia Picos
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  3. Oscar Montiel
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  4. Oscar Castillo
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Corresponding author

Correspondence to Oscar Montiel .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Patricia Melin

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Orozco-Rosas, U., Picos, K., Montiel, O., Castillo, O. (2021). GPU Accelerated Membrane Evolutionary Artificial Potential Field for Mobile Robot Path Planning. In: Castillo, O., Melin, P. (eds) Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications. Studies in Computational Intelligence, vol 940. Springer, Cham. https://doi.org/10.1007/978-3-030-68776-2_13

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