rpng/open_vins

Health v2 · maintenance only

Flags: no_readme

Adoption not part of the score

3057 stars · 917 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OpenVINS is an open-source C++ platform for visual-inertial navigation research, centered on a filter-based (MSCKF/EKF) estimator that fuses inertial measurements with sparse visual feature tracks. It includes a core computer vision library, a multi-sensor simulator, evaluation tooling, and runs with ROS1/ROS2, ROS-free, or in Docker.

Use cases

• run visual-inertial odometry on a camera and IMU dataset
• estimate camera and IMU trajectory with an EKF-based VIO system
• calibrate a visual-inertial sensor rig
• simulate synthetic IMU and camera measurements for research
• evaluate and plot VIO estimation results for a paper
• build a SLAM or state-estimation prototype on top of a modular filter framework

When to choose

• you need a state-of-the-art filter-based (MSCKF) visual-inertial odometry estimator
• you are doing robotics or navigation research and want modular, well-documented code
• you want ROS1/ROS2, ROS-free, or Docker deployment options
• you need sensor calibration, simulation, and evaluation tooling in one platform

When to avoid

• you need a full SLAM system with loop closure and persistent mapping
• you require a permissively licensed library (it is GPL-3.0)
• you want an optimization-based (graph) VIO backend rather than a filter
• you need a plug-and-play production solution with no C++ or robotics background

Facets

library · maturity active

computer-vision simulation testing math robotics computer-vision autonomous-vehicles cpp cross-platform visual-inertial-odometry slam msckf ekf sensor-fusion state-estimation ros research-platform sensor-calibration algorithms linux docker

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