An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 7 of its 12 references that are in the map. First posted on arXiv 1 Apr 2021.
Builds on
7 of 12 references.
References · 7
- 2016ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Camerascited by 801
- 2015On-Manifold Preintegration for Real-Time Visual-Inertial Odometrycited by 95
- 2018Navion: A 2mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Dronescited by 14
- 2020A Survey of FPGA-Based Robotic Computingcited by 8
- 2019eSLAM: An Energy-Efficient Accelerator for Real-Time ORB-SLAM on FPGA Platformcited by 7
- 2017FPGA-based ORB Feature Extraction for Real-Time Visual SLAMcited by 5
- 2020Eudoxus: Characterizing and Accelerating Localization in Autonomous Machinescited by 5
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Citing papers per year: 2021: 1.
1 paper.