Problem
Research questions and friction points this paper is trying to address.
Visual-Inertial Odometry
GPU Acceleration
Cross-platform
CUDA Limitation
State Estimation
VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan
🤖 AI Summary
This study addresses the limited cross-platform deployment of visual-inertial odometry (VIO) caused by its reliance on CUDA, proposing the first Vulkan API-based, cross-platform GPU-accelerated VIO framework. By leveraging Vulkan’s low-level parallel computing capabilities to restructure core VIO algorithms, this method overcomes hardware ecosystem barriers and enables efficient acceleration across heterogeneous devices. Experimental results demonstrate that the proposed system outperforms conventional CUDA-based approaches on multiple platforms, significantly reducing execution latency and power consumption while preserving estimation accuracy. Ultimately, this work establishes a new paradigm for the real-time, platform-agnostic deployment of VIO systems.
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Visual-Inertial Odometry
Vulkan API
Cross-platform GPU Acceleration
Real-time SLAM
Robotics and XR
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