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An Embedded Multi-Sensor Data Fusion Design for Vehicle Perception Tasks

Abstract : Nowadays, multi-sensor architectures are popular to provide a better understanding of environment perception for intelligent vehicles. Using multiple sensors to deal with perception tasks in a rich environment is a natural solution. Most of the research works have focused on PC-based implementations for perception tasks and very few concerns have been addressed for customized embedded designs. In this paper, we propose a Multi-Sensor Data Fusion (MSDF) embedded design for vehicle perception tasks using stereo camera and Light Detection and Ranging (LIDAR) sensors. A modular and scalable architecture based on Zynq-7000 SoC was designed.
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https://hal-uphf.archives-ouvertes.fr/hal-03400988
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Submitted on : Monday, October 25, 2021 - 11:21:54 AM
Last modification on : Tuesday, November 16, 2021 - 3:07:17 AM

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Mokhtar Bouain, Karim Mohamed Abedallah Ali, Denis Berdjag, Nizar Fakhfakh, Rabie Ben Atitallah. An Embedded Multi-Sensor Data Fusion Design for Vehicle Perception Tasks. Journal of Communications, Academy Publisher, 2018, 13 (1), pp.8-14. ⟨10.12720/jcm.13.1.8-14⟩. ⟨hal-03400988⟩

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