Issue |
E3S Web Conf.
Volume 229, 2021
The 3rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)
|
|
---|---|---|
Article Number | 01023 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/e3sconf/202122901023 | |
Published online | 25 January 2021 |
Evaluation of Bio-inspired SLAM algorithm based on a Heterogeneous System CPU-GPU
1
LISTI, ENSA Ibn Zohr University Agadir, 80000, Morocco
2
SATIE, Digiteo Labs, Paris-Sud University, Paris Saclay University, Orsay, France
Localization and mapping are a real problem in robotics which has led the robotics community to propose solutions for this problem... Among the competitive axes of mobile robotics there is the autonomous navigation based on simultaneous localization and mapping (SLAM) algorithms: in order to have the capacity to track the localization and the cartography of robots, that give the machines the power to move in an autonomous environment. In this work we propose an implementation of the bio-inspired SLAM algorithm RatSLAM based on a heterogeneous system type CPU-GPU. The evaluation of the algorithm showed that with C/C++ we have an executing time of 170.611 ms with a processing of 5 frames/s and for the implementation on a heterogeneous system we used CUDA as language with an execution time of 160.43 ms.
Key words: SLAM / RatSLAM / Heterogeneous system / CPU-GPU / C/C++ / CUDA.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.