Code for VINS-Mono is now available on GitHub

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


EuRoC dataset

Code for VINS-Mobile is now available on GitHub

VINS-Mobile is a real-time monocular visual-inertial state estimator developed by members of the HKUST Aerial Robotics Group. It runs on compatible iOS devices, and provides localization services for augmented reality (AR) applications. It is also tested for state estimation and feedback control for autonomous drones. VINS-Mobile uses sliding window optimization-based formulation for providing high-accuracy visual-inertial odometry with automatic initialization and failure recovery. The accumulated odometry errors are corrected in real-time using global pose graph SLAM. An AR demonstration is provided to showcase its capability.

Authors: Peiliang Li, Tong Qin, Zhenfei Yang, Kejie Qiu, and Shaojie Shen


HKUST Aerial Robotics Group

Welcome to the HKUST Aerial Robotics Group led by Prof. Shaojie Shen. Our group is part of the HKUST Robotics Institute.

We develop fundamental technologies to enable aerial robots (or UAVs, drones, etc.) to autonomously operate in complex environments. Our research spans the full stack of aerial robotic systems, with focus on state estimation, mapping, trajectory planning, multi-robot coordination, and testbed development using low-cost sensing and computation components.

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