HydraMini: An FPGA-based Affordable Research and Education Platform for Autonomous Driving

Abstract

Autonomous driving has been a hot topic recently, so many industrial and academic groups are putting much engineering and research efforts into this topic. However, it is difficult for most researchers or students to afford a car as a research platform to conduct experiments for autonomous driving. Further, we believe that only when more people have the chance to make contributions will this area be more prosperous. Therefore, in this paper, we present HydraMini, an affordable experimental research and education platform supporting the experiments from hardware systems to vision algorithms, and its high flexibility makes it easily extended and modified. It is equipped with the Xilinx PYNQ-Z2 board as the computing platform, which deploys the Deep Learning Processing Unit (DPU) in FPGA to accelerate the deep learning inference. It also provides useful tools like a simulator for model training and testing in a virtual environment to facilitate the use of HydraMini. Our platform will help researchers and students build and test their own solutions for autonomous driving algorithms and systems easily and efficiently.