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Single- and Multi-FPGA Acceleration of Dense Stereo Vision for Planetary Rovers

Single- and Multi-FPGA Acceleration of Dense Stereo Vision for Planetary Rovers Increased mobile autonomy is a vital requisite for future planetary exploration rovers. Stereo vision is a key enabling technology in this regard, as it can passively reconstruct in three dimensions the surroundings of a rover and facilitate the selection of science targets and the planning of safe routes. Nonetheless, accurate dense stereo algorithms are computationally demanding. When executed on the low-performance, radiation-hardened CPUs typically installed on rovers, slow stereo processing severely limits the driving speed and hence the science that can be conducted in situ. Aiming to decrease execution time while increasing the accuracy of stereo vision embedded in future rovers, this article proposes HW/SW co-design and acceleration on resource-constrained, space-grade FPGAs. In a top-down approach, we develop a stereo algorithm based on the space sweep paradigm, design its parallel HW architecture, implement it with VHDL, and demonstrate feasible solutions even on small-sized devices with our multi-FPGA partitioning methodology. To meet all cost, accuracy, and speed requirements set by the European Space Agency for this system, we customize our HW/SW co-processor by design space exploration and testing on a Mars-like dataset. Implemented on Xilinx Virtex technology, or European NG-MEDIUM devices, the FPGA kernel processes a 1,120 1,120 stereo pair in 1.7s3.1s, utilizing only 5.49.3 LUT6 and 200312 RAMB18. The proposed system exhibits up to 32 speedup over desktop CPUs, or 2,810 over space-grade LEON3, and achieves a mean reconstruction error less than 2cm up to 4m depth. Excluding errors exceeding 2cm (which are less than 4% of the total), the mean error is under 8mm. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Embedded Computing Systems (TECS) Association for Computing Machinery

Single- and Multi-FPGA Acceleration of Dense Stereo Vision for Planetary Rovers

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2019 ACM
ISSN
1539-9087
eISSN
1558-3465
DOI
10.1145/3312743
Publisher site
See Article on Publisher Site

Abstract

Increased mobile autonomy is a vital requisite for future planetary exploration rovers. Stereo vision is a key enabling technology in this regard, as it can passively reconstruct in three dimensions the surroundings of a rover and facilitate the selection of science targets and the planning of safe routes. Nonetheless, accurate dense stereo algorithms are computationally demanding. When executed on the low-performance, radiation-hardened CPUs typically installed on rovers, slow stereo processing severely limits the driving speed and hence the science that can be conducted in situ. Aiming to decrease execution time while increasing the accuracy of stereo vision embedded in future rovers, this article proposes HW/SW co-design and acceleration on resource-constrained, space-grade FPGAs. In a top-down approach, we develop a stereo algorithm based on the space sweep paradigm, design its parallel HW architecture, implement it with VHDL, and demonstrate feasible solutions even on small-sized devices with our multi-FPGA partitioning methodology. To meet all cost, accuracy, and speed requirements set by the European Space Agency for this system, we customize our HW/SW co-processor by design space exploration and testing on a Mars-like dataset. Implemented on Xilinx Virtex technology, or European NG-MEDIUM devices, the FPGA kernel processes a 1,120 1,120 stereo pair in 1.7s3.1s, utilizing only 5.49.3 LUT6 and 200312 RAMB18. The proposed system exhibits up to 32 speedup over desktop CPUs, or 2,810 over space-grade LEON3, and achieves a mean reconstruction error less than 2cm up to 4m depth. Excluding errors exceeding 2cm (which are less than 4% of the total), the mean error is under 8mm.

Journal

ACM Transactions on Embedded Computing Systems (TECS)Association for Computing Machinery

Published: Mar 18, 2019

Keywords: Planetary rovers

References