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.
CITATION STYLE
Orozco-Rosas, U., Montiel, O., & Sepúlveda, R. (2017). An optimized GPU implementation for a path planning algorithm based on parallel pseudo-bacterial potential field. In Studies in Computational Intelligence (Vol. 667, pp. 477–492). Springer Verlag. https://doi.org/10.1007/978-3-319-47054-2_31
Mendeley helps you to discover research relevant for your work.