An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform

2021/04/01 by Wan, Zishen, Zhang, Yuyang, Raychowdhury, Arijit +3 · 1 citation
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Hardware Architecture (cs.AR) #Robotics (cs.RO)

paper · doi:10.48550/arxiv.2104.00192

Abstract

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 5.6x and 3.4x speedup, as well as 3.0x and 34.6x power reduction, respectively.

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