Navion: A Fully Integrated Energy-Efficient Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones
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2018_preprint_navion.pdf
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Author(s)
Suleiman, Amr AbdulZahir
Zhang, Zhengdong
Carlone, Luca
Karaman, Sertac
Sze, Vivienne
Date Issued
June 2018
Journal
IEEE Symposium on VLSI Circuits
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Suleiman, Amr et al. "Navion: A Fully Integrated Energy-Efficient Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones." IEEE Symposium on VLSI Circuits, 18-22 June, 2018, Honolulu, Hawaii, IEEE, 2018.
Version
Author's final manuscript
Abstract
This paper presents Navion, an energy-efficient accelerator for visual-inertial odometry (VIO) that enables autonomous navigation of miniaturized robots (e.g., nano drones), and virtual/augmented reality on portable devices. The chip uses inertial measurements and mono/stereo images to estimate the
drone’s trajectory and a 3D map of the environment. This estimate is obtained by running a state-of-the-art algorithm based on non-linear factor graph optimization, which requires large irregularly structured memories and heterogeneous computation flow. To reduce the energy consumption and footprint, the entire VIO system is fully integrated on chip to eliminate costly off-chip processing and storage. This work uses compression and exploits
both structured and unstructured sparsity to reduce on-chip memory size by 4.1x. Parallelism is used under tight area constraints to increase throughput by 43%. The chip is fabricated in 65nm CMOS, and can process 752x480 stereo images at up to 171 fps and inertial measurements at up to 52 kHz, while consuming an average of 24mW. The chip is configurable to maximize accuracy, throughput and energy-efficiency across different environments. To the best of our knowledge, this is the first fully integrated VIO system in an ASIC. Keywords: VIO, localization, mapping, nano drones, navigation
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
http://vlsisymposium.org/wp-content/uploads/2018/06/18-glance-web-combined.pdf
