Parallel Bacterial Potential Field Algorithm for Path Planning in Mobile Robots: A GPU Implementation

  • Ulises Orozco-RosasEmail author
  • Oscar Montiel
  • Roberto Sepúlveda
Part of the Studies in Computational Intelligence book series (SCI, volume 749)


Path planning is a fundamental task in autonomous mobile robot navigation and one of the most computationally intensive tasks. In this work, a parallel version of the bacterial potential field (BPF) method for path planning in mobile robots is presented. The BPF is a hybrid algorithm, which makes use of a bacterial evolutionary algorithm (BEA) with the artificial potential field (APF) method, to take advantage of intelligent and classical methods. The parallel bacterial potential field (parallel-BPF) algorithm is implemented on a graphics processing unit (GPU) to speed up the path planning computation in mobile robot navigation. Simulation results to validate the analysis and implementation are provided; the experiments were specially designed to show the effectiveness and the efficiency of the parallel-BPF algorithm.


Bacterial potential field Path planning Mobile robots GPU 



We thank Instituto Politécnico Nacional (IPN), the Comisión de Operación y Fomento de Actividades Academicas 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 2018

Authors and Affiliations

  • Ulises Orozco-Rosas
    • 1
    Email author
  • Oscar Montiel
    • 1
  • Roberto Sepúlveda
    • 1
  1. 1.Centro de Investigación y Desarrollo de Tecnología Digital (IPN-CITEDI), Instituto Politécnico NacionalTijuanaMexico

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