A Robust and Versatile Monocular Visual-Inertial State Estimator

VINS-Mono is a real-time SLAM framework for Monocular Visual-Inertial Systems. It uses an optimization-based sliding window formulation for providing high-accuracy visual-inertial odometry. It features efficient IMU pre-integration with bias correction, automatic estimator initialization, online extrinsic calibration, failure detection and recovery, loop detection, and global pose graph optimization. VINS-Mono is primarily designed for state estimation and feedback control of autonomous drones, but it is also capable of providing accurate localization for AR applications. This code runs on Linux, and is fully integrated with ROS. For iOS mobile implementation, please go to VINS-Mobile.

Authors: Tong Qin, Peiliang Li, Zhenfei Yang, and Shaojie Shen from the HUKST Aerial Robotics Group

Code: https://github.com/HKUST-Aerial-Robotics/VINS-Mono

Videos:

EuRoC dataset

Indoor and outdoor performance

AR application

MAV application

Mobile implementation

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