PhD in Vision-based Simultaneous Localization and Mapping

at  Springer Nature

PHD IN VISION-BASED SIMULTANEOUS LOCALIZATION AND MAPPING

Employer
Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg
Location
Luxembourg
Salary
Negotiable
Closing date
4 Jun 2024
Discipline
Computing, Engineering, Mathematics
Job Type
PhD Position
Employment - Hours
Full time
Duration
Fixed term
Qualification
Masters
Sector
Academia

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The successful candidate will join the Automation & Robotics Research Group (ARG) to pursue a Ph.D. degree (Doctorate) in Computer Science and Computer Engineering (CSCE) under the supervision of Dr. Jose Luis SANCHEZ-LOPEZ.
The position holder will work under the umbrella of a partnership project Theia with the Luxembourg-based company GAMMA AR, developing a solution for real-time vision-based Simultaneous Localization and Mapping (SLAM) of a hand-held tablet on real construction sites (i.e. as-built), with drift-free alignment with existing Building Information Management (BIM) data (i.e. as-planned). This solution will extend our novel Situational Graphs (S-Graphs), concretely our Informed S-Graphs and our Vision-based S-Graphs. Concretely, the main scientific challenges are the (1) vision-based global localization of the hand-held device within BIM (i.e. global alignment between the real construction site and the BIM) when the main structural elements (e.g. walls) are built and there are no major deviations from the BIM. (2) vision-based individual alignment between the main elements of the construction site and BIM, when there are no major deviations. And (3) vision-based global and individual alignment between the construction site and its main elements and BIM in the presence of deviations. The solution will be validated experimentally in real datasets and real construction sites (together with their BIM). On top of this, the solution will be integrated into our ready-to-use robotic platforms to demonstrate its potential use in autonomous robot systems in real-world use cases.

The position holder will be required to perform the following tasks:

• Conducting research on perception and situation understanding, making contributions to the state-of-the-art in the fields of simultaneous localization and mapping (SLAM), computer vision, machine learning, robotics, and/or related
• Proposing and implementing working novel solutions validated in real datasets and real construction sites and our robotic platforms
• Contributing to the development of the solution and its technological demonstration envisaged on the partnership project Theia with Gamma AR
• Contributing to the success and impact of the partnership project Theia with Gamma AR
• Contributing to the research line of situational awareness for robots and autonomous systems of the ARG
• Disseminating results through scientific publications in top peer-reviewed international journals, such as IEEE RA-L, and Elsevier RAS, and conferences, such as ICRA, and IROS