Welcome to the site of the Northern Robotics Laboratory (norlab) at Laval University. Our research laboratory is specialized in mobile and autonomous systems working in northern or difficult conditions. We aim at investigating new challenges related to navigation algorithms to push the boundary of what is currently possible to achieve with a mobile robot in real-life conditions. The current focus of the laboratory is on localization algorithms designed for laser sensors (lidar) and 3D reconstruction of the environment. We will use this website to showcase our results and to simplify the knowledge transfer with some general tips & tricks.
News
:
Four internships in robotics for the summer 2021 all taken!
Norlab is opening four internships covering multiple fields of study for this summer. Apply as soon as you can, we are closing the openings soon. Here is the...
:
New Year 2021 brought us the ROSA project
In the beginning of this year, we have started working with the industrial partner Hydro-Quebec on the new project ROSA (Robot Optimizations for Surveillance...
:
Project SNOW update: Better mapping for Lidar Teach & Repeat capability
In the context of the second milestone of the Snow project, we want to expand and improve our mapping system.
Research
:
Norlab robots
The list of our robots is growing, see for yourself! We like them rugged bacause they often go outdoors, collecting datasets, capturing lidar maps and drivin...
:
Norlab in media!
We are happy that Norlab is being noticed in media. See what they have written about us.
:
Project SNOW
Self-driving cars are expected on our roads soon. In the project SNOW (Self-driving Navigation Optimized for Winter), we focus on the unexplored problem of a...
:
DARPA - SUBTERRANEAN CHALLENGE
DARPA - Subterranean Challenge (DARPA-SubT) is an international robotics competition focusing on autonomy, perception, networking, mobility technologies, and...
:
The Montmorency dataset
This large scale forest mapping dataset in now available for download on Academic Torrents. The dataset contains the ground truth species, diameter at breast...
Publications
:
Lidar Scan Registration Robust to Extreme Motions
Registration algorithms, such as Iterative Closest Point (ICP), have proven effective in mobile robot localization algorithms over the last decades. However,...
:
Accurate outdoor ground truth based on total stations
In robotics, accurate ground-truth position fostered the development of mapping and localization algorithms through creation of cornerstone datasets. In outd...
:
Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned
Challenges inherent to autonomous wintertime navigation in forests include lack of reliable a Global Navigation Satellite System (GNSS) signal, low feature c...
:
Improving the Iterative Closest Point Algorithm using Lie Algebra
Mapping algorithms that rely on registering point clouds inevitably suffer from local drift, both in localization and in the built map. Applications that req...