TY - GEN
T1 - An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform
AU - Wan, Zishen
AU - Zhang, Yuyang
AU - Raychowdhury, Arijit
AU - Yu, Bo
AU - Zhang, Yanjun
AU - Liu, Shaoshan
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/6/6
Y1 - 2021/6/6
N2 - In our past few years' of commercial deployment experiences, we identify localization as a critical task in autonomous machine applications, and a great acceleration target. In this paper, based on the observation that the visual frontend is a major performance and energy consumption bottleneck, we present our design and implementation of an energy-efficient hardware architecture for ORB (Oriented-Fast and Rotated-BRIEF) based localization system on FPGAs. To support our multi-sensor autonomous machine localization system, we present hardware synchronization, frame-multiplexing, and parallelization techniques, which are integrated in our design. Compared to Nvidia TX1 and Intel i7, our FPGA-based implementation achieves 5.6\times and 3.4\times speedup, as well as 3.0\times and 34.6\times power reduction, respectively.
AB - In our past few years' of commercial deployment experiences, we identify localization as a critical task in autonomous machine applications, and a great acceleration target. In this paper, based on the observation that the visual frontend is a major performance and energy consumption bottleneck, we present our design and implementation of an energy-efficient hardware architecture for ORB (Oriented-Fast and Rotated-BRIEF) based localization system on FPGAs. To support our multi-sensor autonomous machine localization system, we present hardware synchronization, frame-multiplexing, and parallelization techniques, which are integrated in our design. Compared to Nvidia TX1 and Intel i7, our FPGA-based implementation achieves 5.6\times and 3.4\times speedup, as well as 3.0\times and 34.6\times power reduction, respectively.
UR - http://www.scopus.com/inward/record.url?scp=85106075065&partnerID=8YFLogxK
U2 - 10.1109/AICAS51828.2021.9458486
DO - 10.1109/AICAS51828.2021.9458486
M3 - Conference contribution
AN - SCOPUS:85106075065
T3 - 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021
BT - 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021
Y2 - 6 June 2021 through 9 June 2021
ER -
