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

—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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