Implementation of FastSLAM2.0 on an Embedded System and HIL Validation using Different Sensors Data

Implementation of FastSLAM2.0 on an Embedded System and HIL Validation using Different Sensors Data

Abouzahir Mohamed, Elouardi Abdelhafid, Bouaziz Samir, Latif Rachid, Tajer Abdelouahed
Copyright: © 2015 |Volume: 6 |Issue: 2 |Pages: 29
ISSN: 1947-9220|EISSN: 1947-9239|EISBN13: 9781466678484|DOI: 10.4018/IJARAS.2015070105
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MLA

Mohamed, Abouzahir, et al. "Implementation of FastSLAM2.0 on an Embedded System and HIL Validation using Different Sensors Data." IJARAS vol.6, no.2 2015: pp.88-116. http://doi.org/10.4018/IJARAS.2015070105

APA

Mohamed, A., Abdelhafid, E., Samir, B., Rachid, L., & Abdelouahed, T. (2015). Implementation of FastSLAM2.0 on an Embedded System and HIL Validation using Different Sensors Data. International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS), 6(2), 88-116. http://doi.org/10.4018/IJARAS.2015070105

Chicago

Mohamed, Abouzahir, et al. "Implementation of FastSLAM2.0 on an Embedded System and HIL Validation using Different Sensors Data," International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS) 6, no.2: 88-116. http://doi.org/10.4018/IJARAS.2015070105

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Abstract

The improved particle filter based simultaneous localization and mapping (SLAM) has been developed for many robotic applications. The main purpose of this article is to demonstrate that recent heterogeneous architectures can be used to implement the FastSLAM2.0 and can greatly help to design embedded systems based robot applications and autonomous navigation. The algorithm is studied, optimized and evaluated with a real dataset using different sensors data and a hardware in the loop (HIL) method. Authors have implemented the algorithm on a system based embedded applications. Results demonstrate that an optimized FastSLAM2.0 algorithm provides a consistent localization according to a reference. Such systems are suitable for real time SLAM applications.

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