[Submitted on 24 Sep 2026]
Title:VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan
View a PDF of the paper titled VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan, by Ole Hoffmann and 2 other authors
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Abstract: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.
Subjects:
Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2609.30459 [cs.RO]
(or arXiv:2609.30459v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2609.30459
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Mateo De Mayo [view email] [v1] Thu, 24 Sep 2026 18:50:48 UTC (3,784 KB)
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