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 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...
Three articles accepted at ICRA 2019!
We are happy to announce that we have three accepted publications at the 2019 International Conference on Robotics and Automation.
First sensor from RoboSense in Quebec!
The laboratory received recently a RS-LIDAR-16 from RoboSense. This is the first unit delivered in Quebec and we are happy to use it for our project on 3D ma...
Undergraduate Student Research Awards
Congratulation to Simon-Pierre Deschênes for his Undergraduate Student Research Awards (USRA). We are welcoming this addition to the team during this summer!
Exploration of large caves is challenging using traditional mapping tools. There are limited places to install a tripod equipped with a highly accurate lidar...
Open position for a Ph.D. student!
Libpointmatcher is a library that implements the Iterative Closest Point (ICP) algorithm for alignment of point clouds. It supports both point-to-point and ...
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...
Predicting GNSS satellite visibility from dense point clouds
To help future mobile agents plan their movement in harsh environments,a predictive model has been designed to determine what areas would be favorable for Gl...