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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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Submitted on : Wednesday, November 3, 2021 - 8:36:41 AM
Last modification on : Tuesday, November 16, 2021 - 10:41:24 AM


  • HAL Id : hal-03412391, version 1



Mokhtar Bouain, Karim Mohamed Abedallah Ali, Denis Berdjag, Nizar Fakhfakh, Rabie Ben Atitallah. An Embedded Multi-Sensor Data Fusion Design for Vehicle Perception Tasks. ICCSIT 2017 : 2017 10th International Conference on Computer Science and Information Technology (ICCSIT 2017), Oct 2017, Florence, Italy. ⟨hal-03412391⟩



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