@inbook{b9a505cf151b40d19e62679be5724c54,
title = "An optimized GPU implementation for a path planning algorithm based on parallel pseudo-bacterial potential field",
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 = "GPU, Mobile robots, Path planning, Pseudo-bacterial potential field",
author = "Ulises Orozco-Rosas and Oscar Montiel and Roberto Sep{\'u}lveda",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.",
year = "2017",
doi = "10.1007/978-3-319-47054-2_31",
language = "Ingl{\'e}s",
series = "Studies in Computational Intelligence",
publisher = "Springer Verlag",
pages = "477--492",
booktitle = "Studies in Computational Intelligence",
address = "Alemania",
}