LEVIO: リソース制約デバイス向け軽量組み込み視覚慣性オドメトリ
LEVIO: Lightweight Embedded Visual Inertial Odometry for Resource-Constrained Devices
超低消費電力の組み込み向けに最適化した視覚慣性オドメトリパイプラインLEVIOを提案し、RISC-V SoC上で20FPS・100mW未満のリアルタイム動作を実現した。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Jonas Kühne, Christian Vogt, Michele Magno, Luca Benini
分類: cs.CV, cs.RO, eess.IV
原文アブストラクト
Accurate, infrastructure-less sensor systems for motion tracking are essential for mobile robotics and augmented reality (AR) applications. The most popular state-of-the-art visual-inertial odometry (VIO) systems, however, are too computationally demanding for resource-constrained hardware, such as micro-drones and smart glasses. This work presents LEVIO, a fully featured VIO pipeline optimized for ultra-low-power compute platforms, allowing six-degrees-of-freedom (DoF) real-time sensing. LEVIO incorporates established VIO components such as Oriented FAST and Rotated BRIEF (ORB) feature tracking and bundle adjustment, while emphasizing a computationally efficient architecture with parallelization and low memory usage to suit embedded microcontrollers and low-power systems-on-chip (SoCs). The paper proposes and details the algorithmic design choices and the hardware-software co-optimization approach, and presents real-time performance on resource-constrained hardware. LEVIO is validated on a parallel-processing ultra-low-power RISC-V SoC, achieving 20 FPS while consuming less than 100 mW, and benchmarked against public VIO datasets, offering a compelling balance between efficiency and accuracy. To facilitate reproducibility and adoption, the complete implementation is released as open-source.
