Open-Source Educational Platform for FPGA Accelerated AI in Robotics

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Abstrakt

Artificial Intelligence (AI) using neural networks is growing rapidly in the area of robotics and many tools have been developed in the last few years to utilize these networks. However, these tools are very abstract and do not provide deep knowledge on how the neural networks perform their computations. This makes it difficult for roboticists to understand and fully harness the power of AI. In this work, we present an open-source framework for designing and implementing a simple neural network targeting edge computing platforms. The framework goes step-by-step through the training, synthesis, and hardware implementation on a Zynq platform. The final hardware implementation is evaluated against a classical implementation in software. The platform was used in the Embedded Systems Course at the University of Southern Denmark.

OriginalsprogEngelsk
Titel2022 8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022
ForlagIEEE
Publikationsdato2022
Sider112-115
ISBN (Elektronisk)9781665483773
DOI
StatusUdgivet - 2022
Begivenhed8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022 - Virtual, Munich, Tyskland
Varighed: 10. feb. 202212. feb. 2022

Konference

Konference8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022
Land/OmrådeTyskland
ByVirtual, Munich
Periode10/02/202212/02/2022
Navn2022 8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022

Bibliografisk note

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 861111, Drones4Safety.

Publisher Copyright:
© 2022 IEEE.

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