Category: Uncategorized

Colloque REPARTI Workshop 2024: Tuesday, May 21, 2024, 10:15 am – 4:30 pm, Pavillon Alphonse-Desjardins, Université Laval

A keynote presentation in the morning, followed by a poster session offered by REPARTI students and a tour of three research labs in the afternoon. This one-day Workshop will allow you to learn more about the research projects and initiatives carried out by REPARTI members. Here is the program which will be updated regularly to provide all of the information about the keynote presentation, poster session and lab visits:

Colloque REPARTI 2024 Program
The program provides information about the morning keynote presentation, the student poster session and the lab visits.

Here are the photos which were taken at the REPARTI Workshop on May 21, 2024. Many thanks to Guillaume Villeneuve, photographer.
https://www.flickr.com/photos/baby_tux/albums/72177720317238821

Colloque REPARTI 2023: Tuesday, May 23, 2023, 10:15 am – 4:30 pm, Pavillon Alphonse-Desjardins, Université Laval

A keynote presentation in the morning, followed by a poster session offered by REPARTI students in the afternoon. This one-day Workshop will allow you to learn more about the research projects and initiatives carried out by REPARTI members. Here is the detailed program which includes information about the keynote presentation and the poster session:

Colloque REPARTI 2023 Program
The program provides detailed information about the morning keynote presentation and the posters that will be presented in the afternoon.

Keynote Presentation, 11 am – 12 pm

PHOTO
Benoit Gosselin, PhD, ing., Fellow CAE
Canada Research Chair in Smart Biomedical Microsystems
Department of Electrical and Computer Engineering Engineering
Université Laval
Email: benoit.gosselin@gel.ulaval.ca

Title: AI-enabled sensors for advanced neuroengineering and personalized healthcare applications

Short Abstract:
This presentation covers the design of intelligent biomedical systems incorporating machine learning and on-chip data analysis methods. On-chip strategies are presented to perform in-sensor data analysis to avoid delays and latency, enabling real-time, closed-loop interaction with biomedical systems including wearable sensors and brain-machine interfaces.

Short Biography:
Benoit Gosselin is a professor in the Department of Electrical and Computer Engineering at Université Laval and holds the Canada Research Chair in Smart Biomedical Microsystems. His research focuses on the design of intelligent bioelectronic systems for brain-computer interfaces, neuroengineering and wearable devices for personalized health care. Professor Gosselin is an Associate Editor of the IEEE Transactions on Biomedical Circuits and Systems, IEEE Sensors Journal and Frontiers in Neuroscience. He is a Fellow of the Canadian Academy of Engineering and the recipient of several awards, including the NSERC Brockhouse of Canada Award and the Genie Innovation Award from the Ordre des ingénieurs du Québec. His significant research contributions have led to the commercialization of the first wireless electro-optic bio-implant to study the development of brain diseases in real time.

Poster session, 1:30 – 4:30 pm:
Please see the program for the list of the 30 posters that will be presented:
Colloque REPARTI 2023 Program

For more details, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

REPARTI Webinar:
Parallel robots with reconfigurable effectors:
theory and applications

Patrice Lambert
Assistant Professor in Robotics and Automation
Laboratoire de robotique
Dép. de génie mécanique, U. Laval

Friday, December 16, 2022, 12 p.m.

Abstract
Parallel robots are traditionally composed of two rigid bodies, the base and the effector, connected in parallel by independent kinematic chains, referred to as legs. Normally, one joint per leg near the base is operated to allow control of the effector. Reconfigurable end-effectors replace the rigid body of the end-effector with one or more closed kinematic chains, having internal degrees of freedom, which can be used for grasping. The movements and configuration of the effector are all controlled by the leg actuators. During this presentation, general notions on parallel robots with reconfigurable effectors will be introduced, and the design and implementation of three haptic devices, having from 5 to 7 degrees of freedom, based on this concept will be discussed.

Biography
Patrice Lambert is an Assistant Professor in Robotics and Automation in the Department of Mechanical Engineering in the Faculty of Science and Engineering. He holds a Bachelor’s degree in Engineering Physics and a Master’s degree in Aerospace Engineering from Université Laval as well as a Ph.D. in Robotics from the Delft University of Technology, in the Netherlands. He worked as a postdoctoral researcher in the Netherlands until 2017, then as a Research Fellow at King’s College London, UK until 2022. His research work covers various areas of robotics, including haptic devices, parallel and cable robots, robotic grippers and fundamental aspects of mechanisms and linkages.

The presentation will be given in French and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

REPARTI Workshop 2022: Friday, May 13, 2022, 8h45 – 15h15, on Zoom* within the Acfas Conference.

Three keynote presentations, each followed by a series of short presentations, all of which are offered by researchers and students from the member institutions of REPARTI, will allow you to learn more about the research projects and initiatives carried out by REPARTI members. Here is the detailed program which includes the titles of all of the presentations:

REPARTI Workshop 2022 Program

*To obtain the Zoom meeting web link, please access the Acfas website, https://www.acfas.ca/ and connect to your user account linked to your registration for the Acfas conference. Then go to the Colloque #205 webpage and click on “Accéder à la plateforme”.

CeRVIM-REPARTI Webinar
Parallel and Cable Robotics Research:
Theoretical and Technological Advancements

Hamid D. Taghirad
Advanced Robotics and Automated Systems Lab (ARAS)
K. N. Toosi University of Technology
Tehran, Iran
Visiting Professor, University of Alberta

Date and Time:
Tuesday, March 8, 2022 (17 Esfand 1400)
12:00-13:00 (Eastern Standard Time: -5:00 GMT) or
20:30-21:30 (Iran Standard Time: +3:30 GMT)

Abstract:
Cable and parallel robotics have been gaining more attention among researchers due to their unique characteristics and applications. Simple structure, high payload capacity, agile movements, and deployable structures are the main characteristics that nominate cable-robots from the other types of manipulators for many applications such as imaging, cranes, agriculture, etc. Interdisciplinary research fields such as dynamic analysis and control synthesis of parallel and cable-driven manipulators by using modern and intelligent approaches will be given further consideration in this presentation.

Kamalolmol® robot is a representative of cable-driven robots developed in ARAS research group, which is a fast deployable edutainment cable-driven robot for calligraphy and painting (chiaroscuro) applications. Additionally, ARAS research exploits the simplicity of cable robots with graph-based optimization and perception algorithms to create commercial inspection and imaging tools for various applications. In this webinar, the underlying concepts of such systems and the current state-of-the-art development of these advancements will be presented.

Bio:

Hamid D. Taghirad has received his B.Sc. degree in mechanical engineering from Sharif University of Technology, Tehran, Iran, in 1989, his M.Sc. in mechanical engineering in 1993, and his Ph.D. in electrical engineering in 1997, both from McGill University, Montreal, Canada. He is currently a visiting Professor, University of Alberta, and professor and director of  Advanced Robotics and Automated System (ARAS), K. N. Toosi University of Technology, Tehran, Iran. He is a senior member of IEEE, and Editorial board of International Journal of Robotics: Theory and Application, and International Journal of Advanced Robotic Systems. His research interest is robust and nonlinear control applied to robotic systems. His publications include five books, and more than 300 papers in peer-reviewed international Journals and conference proceedings.

The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

CIM-REPARTI Webinar: Data-Driven Modelling and Control with the Koopman Operator

Steven Dahdah
DECAR Systems group
Centre for Intelligent Machines, CIM
McGill University

Feb. 24, 2022, 12 p.m. – 1 p.m.

Abstract:
Using the Koopman operator, nonlinear systems can be expressed as infinite-dimensional linear systems. Data-driven methods can then be used to approximate a finite-dimensional Koopman operator, which is particularly useful for system identification, control, and state estimation tasks. However, approximating large Koopman operators is numerically challenging, leading to unstable Koopman operators being identified for otherwise stable systems. Presented are a selection of techniques to regularize the Koopman regression problem, including a novel H-infinity norm regularizer. The authors’ open-source Koopman operator identification library, pykoop, is also presented.

Bio:
Steven Dahdah is a Ph.D. student in the department of Mechanical Engineering at McGill University. He is a member of the DECAR systems group, which, under the guidance of Prof. James Richard Forbes, conducts research in the dynamics, estimation, and control of aerospace and robotic systems. He received a B.Eng. in Electrical Engineering from McGill University in 2019. His research explores data-driven modelling and control techniques for industrial robots.

The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

REPARTI Webinar: Résultats de la première participation canadienne au prestigieux DARPA Subterranean Challenge

Prof. François Pomerleau
Directeur, NORLAB
Département d’informatique et de génie logiciel
Université Laval

December 16, 2021, 12 p.m. – 1 p.m.

Abstract

In September 2021, the Grand Final of DARPA Subterranean Challenge was held in Kentucky. The event brought together the largest robotics laboratories from 11 countries with the capacity to deploy a fleet of heterogeneous robots in an unknown, underground environment. These laboratories included representatives from NASA, JPL, Stanford, MIT, ETH Zurich, CMU and the Boreal Robotics Laboratory (Norlab) at Laval University. Thanks to a collaboration with the Center for Robotics and Autonomous Systems (CRAS) of the Czech Technical University (CTU), the team originally named CTU-CRAS-NORLAB was able to take part in the competition and won several honours during the four year duration of the challenge. This was the first Canadian participation in the DARPA robotic challenge which began almost 20 years ago. For more information on the DARPA Subterranean Challenge, visit the following website (https://www.subtchallenge.com), and click on the team: CTU-CRAS-NORLAB

The presentation will briefly explain the history of DARPA robotics challenges and their motivation. Then, a description of the underground environment exploration challenge will be given, as well as a presentation of the solutions deployed by the CTU-CRAS-NORLAB team. The presentation will conclude with a few highlights from the final event as well as some lessons learned from this large-scale experience.

The presentation will be given in French and the slides will be in English.

Bio :
François Pomerleau made his debut in research by interacting with the Canadian Space Agency and the European Space Agency during his studies in Computer Engineering at Sherbrooke University. He obtained his Master’s degree (François Michaud’s Lab) from this university in 2009 after a one-year stay at EPFL (Roland Siegwart Lab – Switzerland) where he worked on an autonomous car prototype. He completed his Ph.D. at ETH Zurich (Roland Siegwart’s Lab- Switzerland) in 2013 during this time he participated in several robotic deployments in uncontrolled environments, including work with European fire brigades and in alpine lakes. After technology transfer activities at Alstom Inspection Robotics and a stay at Laval University (Philippe Giguère’s Lab), he received a postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada to continue his research at the University of Toronto in Mobile Robotics (Tim Barfoot’s Lab). He continued his technological transfer activities as a postdoctoral researcher at Laval University in the Robotics Laboratory (Clément Gosselin’s lab) and worked, in collaboration with the Robotiq company, to develop the Industry 4.0. Since September 2017, he is a professor in the Computer Science and Software Engineering Department at Laval University.

His research interests include 3D reconstruction of environments using laser data, autonomous navigation, search and rescue activities, environmental monitoring, trajectory planning and scientific methodology applied to robotics.

Zoom Meeting
To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

Colloque REPARTI 2021: Wednesday, June 16, 2021, 9h00 – 11h00, on Zoom.*

A keynote presentation, followed by a series of short presentations, offered by researchers and students from the member institutions of REPARTI, will allow you to learn more about the research projects and initiatives carried out by REPARTI members. Here is the detailed program which includes the titles of all of the presentations:

Colloque REPARTI 2021 Program

*To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

REPARTI Webinar:  Ultrasound imaging: let’s talk

Catherine Laporte
Laboratoire de traitement de l’information en santé (LATIS)
École de technologie supérieure (ÉTS)

April 22, 2021, 12:00 – 1:00 p.m.

Abstract

Ultrasound imaging is the fastest growing commercial sector in the medical imaging industry. Non-invasive and highly versatile, ultrasound also allows real-time imaging and is becoming increasingly portable and affordable, which paves the way for a growing number of new applications and users. However, ultrasound images remain difficult to interpret and acquire. My research aims to make ultrasound imaging easier to use for new applications and new users. This presentation will provide an overview of different aspects of my work that are related to this general objective, with an emphasis on my work applied to the study of articulatory phonetics.

The presentation will be given in English and the slides will be in French.

Catherine Laporte is a professor of electrical engineering at École de technologie supérieure since 2010. Her expertise lies in the area of medical image analysis, with a special focus on ultrasound imaging. Her current research aims at improving the usability of ultrasound imaging for new users and new applications. Previously, she obtained her M. Eng. and Ph.D. in computer engineering at McGill University’s Centre for Intelligent Machines, supervised by T. Arbel, and her B. Eng. degree at Polytechnique Montréal.

Zoom Meeting
To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

REPARTI Webinar:  Understanding the world behind the image

Jean-François Lalonde
Laboratoire de Vision et Systèmes Numériques (LVSN)
Dép. de génie électrique et de génie informatique, Université Laval

March 29, 2021, 12:00 – 1:00 p.m.

Abstract

Images are formed through a series of interactions between light, surfaces in the scene (according to their geometry and reflectance) and, ultimately, the camera. Accurate physical models of these interactions exist, but have seen limited applicability in real-world conditions, outside the lab. Because of this, a large fraction of computer vision research treats images as 2D pixel arrays without regard to how they were formed.

In this talk, I instead advocate for the idea of reasoning about the real world behind the image and explicitly consider these light-geometry-camera interactions. To do so, we propose algorithms that understand the 3D geometry, lighting, surface reflectance, and even the camera itself from images. The key idea is to combine physics-based models and machine learning techniques in order to better model, understand, and recreate the richness of our visual world.

The presentation will be given in French and the slides will be in English.

Jean-François Lalonde, Ph.D., is an Associate Professor in the Faculty of Science and Engineering at Université Laval, in the Department of Electrical and Computer Engineering. He is a member of the Institute Intelligence and Data (IID), the Big Data Research Center (CRDM), and the Research Center on Vision, Robotics and Machine Intelligence (CeRVIM) at Université Laval. Previously, he was a Post-Doctoral Associate at Disney Research, Pittsburgh. He received a Ph.D. in Robotics from Carnegie Mellon University in 2011. His thesis, titled Understanding and Recreating Appearance under Natural Illumination, won the CMU School of Computer Science Distinguished Dissertation Award. His research interests lie at the intersection of computer vision, computer graphics, and machine learning.  In particular, he is interested in exploring how physics-based models and data-driven machine learning techniques can be unified to better understand, model, interpret, and recreate the richness of our visual world. His group has captured and published the largest datasets of indoor and outdoor high dynamic range illumination images, freely available for research. He is actively involved in bringing research ideas to commercial products, as demonstrated by his several patents, technology transfers with large companies such as Adobe and Facebook, and involvement with startups including Geomagical Labs (San Francisco, acquired by IKEA) and TandemLaunch (Montreal).

Zoom Meeting
To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca