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2017 | OriginalPaper | Chapter

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

Authors : Ulises Orozco-Rosas, Oscar Montiel, Roberto Sepúlveda

Published in: Nature-Inspired Design of Hybrid Intelligent Systems

Publisher: Springer International Publishing

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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.

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Metadata
Title
An Optimized GPU Implementation for a Path Planning Algorithm Based on Parallel Pseudo-bacterial Potential Field
Authors
Ulises Orozco-Rosas
Oscar Montiel
Roberto Sepúlveda
Copyright Year
2017
Book
Nature-Inspired Design of Hybrid Intelligent Systems

Print ISBN: 978-3-319-47053-5

Electronic ISBN: 978-3-319-47054-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-47054-2_31

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