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.
Norlab goes to CRV!
This month, the lab attended the 17th conference on Computer and Robot Vision, which was held virtually due to the COVID-19 situation.
Our first group photo!
It has been a good year in term of team building and equipment acquisition. Next year will most probably reserve us a lot of surprises, but I’m certain that...
Norlab is going to Asia!
We are going to Tokyo (Japan) and Macau (China) with four accepted publications at the 2019 International Conference on Field and Service Robotics and one at...
First appearance of the lab in IEEE Spectrum
Norlab appears in the online version of the magazine IEEE Spectrum with the title DARPA Subterranean Challenge: Meet the First 9 Teams. They confuse our Fren...
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...
Exploration of large caves is challenging using traditional mapping tools. There are limited places to install a tripod equipped with a highly accurate lidar...
Evaluation of Skid-Steering Kinematic Models for Subarctic Environments
In subarctic and arctic areas, large and heavy skid-steered robots are preferred for their robustness and ability to operate on difficult terrain. State esti...
Large-scale 3D Mapping of Subarctic Forests
The ability to map challenging subarctic environments opens new horizons for robotic deployments in industries such as forestry, surveillance, and open-pit m...
Lambda-Field: A Continuous Counterpart of the Bayesian Occupancy Grid for Risk Assessment
In a context of autonomous robots, one of the most important tasks is to ensure the safety of the robot and its surrounding. The risk of navigation is usuall...
Lidar Measurement Bias Estimation via Return Waveform Modelling in a Context of 3D Mapping
In a context of 3D mapping, it is very important to obtain accurate measurements from sensors. In particular, LIDAR measurements are typically treated as a z...