VkVIO: VulkanによるクロスプラットフォームGPU加速視覚慣性オドメトリ
VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan
CUDAに依存せずVulkan APIを用いてGPU加速する初のクロスプラットフォーム視覚慣性オドメトリ(VIO)手法を提案し、ワークステーションから低価格シングルボードPCまで幅広い機器でCUDAベースを上回る精度とリアルタイム性能を実現した。
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著者: Ole Hoffmann, Mateo de Mayo, Daniel Cremers
分類: cs.RO, cs.CV
原文アブストラクト
Perception in robotics and XR fundamentally relies on good state estimation. Visual-inertial odometry (VIO) and Simultaneous Localization and Mapping (VI-SLAM) are proven ways of achieving this goal in a cost-effective and accurate manner. Efficiency in these systems allows for smaller, cooler, and lighter devices. GPU acceleration is a natural approach for reducing latency, thanks to their wide availability in platforms like embedded computers, mobile phones, and XR headsets. However, previous works in the literature have limited themselves to the use of CUDA for this task, significantly reducing deployment options to a single vendor. We instead leverage the vendor-agnostic Vulkan API, originally designed for the strict performance requirements of 3D graphics applications. In this work, we present VkVIO, the first, to the best of our knowledge, cross-platform GPU-accelerated VIO method. We provide state-of-the-art accuracy with causal estimates required for real-time operation. We deploy VkVIO on a diverse range of devices spanning a workstation, a laptop, and an extremely inexpensive single-board computer, while outperforming CUDA-based systems on the same hardware. VkVIO enables possibilities for low-latency, low-power, and low-cost VIO in robotics and XR.