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An Optimized GPU Implementation for a Path Planning Algorithm Based on Parallel Pseudo-bacterial Potential Field

  • Ulises Orozco-Rosas
  • Oscar Montiel
  • Roberto Sepúlveda
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 667)

Abstract

This work presents a high-performance implementation of a path planning algorithm based on parallel pseudo-bacterial potential field (parallel-PBPF) on a graphics processing unit (GPU) as an improvement to speed up the path planning computation in mobile robot navigation. Path planning is one of the most computationally intensive tasks in mobile robots and the challenge in dynamically changing environments. We show how data-intensive tasks in mobile robots can be processed efficiently through the use of GPUs. Experiments and simulation results are provided to show the effectiveness of the proposal.

Keywords

Path planning Pseudo-bacterial potential field GPU Mobile robots 

Notes

Acknowledgments

We thank to Instituto Politécnico Nacional (IPN), to the Commission of Operation and Promotion of Academic Activities of IPN (COFAA), and the Mexican National Council of Science and Technology (CONACYT) for supporting our research activities.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ulises Orozco-Rosas
    • 1
  • Oscar Montiel
    • 1
  • Roberto Sepúlveda
    • 1
  1. 1.Instituto Politécnico NacionalCentro de Investigación y Desarrollo de Tecnología Digital (CITEDI-IPN)TijuanaMexico

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