Modern autonomous vehicles require efficient and predictable hardware and software to guarantee a high level of safety. Meeting response time deadlines while processing large amounts of sensor data and maintaining a reasonable power consumption is a complex task on embedded devices. Hardware acceleration on FPGA fabric proposes itself as a predictable and certifiable solution to this problem. Research on embedded heterogeneous platforms, however, has a more complex development lifecycle. This paper presents a complete hardware/software platform for autonomous driving research on a commercial off-the-shelf Industrial-Grade FPGA-based MPSoC (an AMD KR260), with a particular focus on autonomous racing use-cases. On the software side, we release the first iteration of our open-source autonomous racing stack based on ROS2. Finally, we present a case-study on a hardware-accelerated 2D LiDAR localization pipeline, which is developed and integrated on the platform. The FPGA implementation provides a 2.64x speed-up over its host counterpart and is released as well as open hardware.
Thundershot: an open-source autonomous vehicles research platform for embedded heterogeneous MPSoCs / Gavioli, F.; Moretti, F.; Russo, A.; Capotondi, A.; Burgio, P.. - 2:(2025), pp. 26-29. ( 22nd ACM International Conference on Computing Frontiers Cagliari, Italy May 28-20, 2025) [10.1145/3706594.3726968].
Thundershot: an open-source autonomous vehicles research platform for embedded heterogeneous MPSoCs
Capotondi A.;Burgio P.
2025
Abstract
Modern autonomous vehicles require efficient and predictable hardware and software to guarantee a high level of safety. Meeting response time deadlines while processing large amounts of sensor data and maintaining a reasonable power consumption is a complex task on embedded devices. Hardware acceleration on FPGA fabric proposes itself as a predictable and certifiable solution to this problem. Research on embedded heterogeneous platforms, however, has a more complex development lifecycle. This paper presents a complete hardware/software platform for autonomous driving research on a commercial off-the-shelf Industrial-Grade FPGA-based MPSoC (an AMD KR260), with a particular focus on autonomous racing use-cases. On the software side, we release the first iteration of our open-source autonomous racing stack based on ROS2. Finally, we present a case-study on a hardware-accelerated 2D LiDAR localization pipeline, which is developed and integrated on the platform. The FPGA implementation provides a 2.64x speed-up over its host counterpart and is released as well as open hardware.| File | Dimensione | Formato | |
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gavioli_CF25.pdf
Open access
Descrizione: Pre-print
Tipologia:
AAM - Versione dell'autore revisionata e accettata per la pubblicazione
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