UROP Project Listing System
 
Project Title:
Robust monocular visual-inertial localization and mapping
Supervisor:SHEN Shaojie
Co-Supervisor:-
Quota:5
Project Description:Monocular visual-inertial systems, which includes only a camera and a low cost inertial measurement unit, is one of the most compact and cost-effective sensing options for robobics and augmented reality applications. This sensor setup is widely available in almost all modern smart phones, and is being deployed for autonomous drones and self-driving cars. In this project, we aim to push the frontier of monocular visual-inertial simultaneous localization and mapping (SLAM), by extending and improving our popular open source VINS-Mono system: https://github.com/HKUST-Aerial-Robotics/VINS-Mono The goal is to develop VINS-Mono into the most robust and versatile SLAM system for a large range of applications running on different computing platforms.
Course type: UROP1100 UROP2100 UROP3100 UROP4100 
Applicant's Roles:* Understand methods and implementations of our existing monocular visual-inertial SLAM system. * Contribute to the continuing development of the system, including robust large loop closure, rolling shutter compensation, online sensor calibration, etc. * Porting of our system to Android and iOS mobile devices * Work together with PG students to conduct challenging experiments. 
Applicant's Learning Objectives:* Learn state-of-the-art methodologies on vision processing pipeline, inertial navigation, sensor fusion, and simultaneous localization and mapping * Learn the methods and implementations of our state-of-the-art VINS-Mono system. * Learn and practice the methodologies for large-scale software development. 
Complexity of the project:Challenging 
 



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