Grant: Research Tools and Instruments
École Polytechnique de Montréal
$142,348.00
Collective Perception in Swarm Robotics
EF 2022-23
Résumé
Automation has been, and still is, the driving force behind the transformation of our economies. However, to this day robots are still mostly relegated to tightly controlled industrial assembly lines, where all their motions are carefully planned and tuned for very specific and limited tasks. Despite the best efforts of scientists and engineers, robots are not yet ready to leave their supervised settings to wander the wild and the unknown. We have been carrying a research program to make swarm robotics technology into practical, every day applications. In the past 6 years, we have produced contributions to connectivity maintenance, long-term autonomy, pattern formation, collaborative localization with minimal infrastructure, multi-robot mapping, object tracking, human-swarm interfaces, space exploration and collaborative transport. These contributions were made possible using robots obtained via previous RTI competitions, that are now in dire need of upgrade and replacement to continue the program. Our current focus is collaborative perception: the need for reliable, resilient and safe perception is a core challenge of autonomous robotics. One of the core perception algorithm in robotics is Simultaneous Localization And Mapping, or SLAM. Situational awareness, as provided by SLAM, is essential to most robotic systems. While it can be done on each robot individually, it is often beneficial to perform it collaboratively when working with groups of robots. In Collaborative SLAM, or C-SLAM, each individual robot performs single-robot SLAM, then communicates and performs data association with the other robots in order to build a common global map between them. This way, they can share a common reference frame for localization and a mutual understanding of the environment for decision-making. Our general objective is to reduce the rate of failures of multi-robot localization and mapping algorithms deployed in unknown and uncontrolled environments. We request a set of 20 AgileX Limo: a small but capable robot featuring a powerful onboard computer, a 3D camera, an inertial unit, and a lidar. Having at least 20 robots would allow us to experiment hierarchical swarms, collaborative transport, energy sufficiency, and collaborative SLAM. We also request 2 Bunker Mini robots to support our research on multi-robot exploration and mapping of GPS-denied environments. Our research output will be tested in collaboration with the European Space Agency (ESA), the Canadian Space Agency (CSA), and NASA JPL. Over the next five years, we expect 6 Postdoctoral fellows, 10 PhDs, 8 Master's and 15 undergraduates from the applicant's laboratory to be trained using this equipment.
Programme
Research Tools and Instruments
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RTI-2023-00281
Name nom
Beltrame, Giovanni
Department département
Génie informatique et génie logiciel - Génie informatique et génie logiciel
Organization id
64
Institution établissement
École Polytechnique de Montréal
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2023
Award amount
142348
Program id
RTI
Program name en
Research Tools and Instruments
Program name fr
Outils et instruments de recherche
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1607
Committee name en
Computer, Mathematical and Statistical Sciences (RTI)
Committee name fr
Sciences informatiques, mathématiques et statistiques (OIR)
Area of application code
513
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Electrical and electronic machinery and equipment (including computer hardware)
Area of application fr
Machinerie et équipement électriques et électroniques (y compris matériel informatique)
Research subject code
2600
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Robotics
Research subject fr
Robotique
Installment
inst:1
Partie
1
Nb partie
1
Application title
Collective Perception in Swarm Robotics
Application summary
Automation has been, and still is, the driving force behind the transformation of our economies. However, to this day robots are still mostly relegated to tightly controlled industrial assembly lines, where all their motions are carefully planned and tuned for very specific and limited tasks. Despite the best efforts of scientists and engineers, robots are not yet ready to leave their supervised settings to wander the wild and the unknown. We have been carrying a research program to make swarm robotics technology into practical, every day applications. In the past 6 years, we have produced contributions to connectivity maintenance, long-term autonomy, pattern formation, collaborative localization with minimal infrastructure, multi-robot mapping, object tracking, human-swarm interfaces, space exploration and collaborative transport. These contributions were made possible using robots obtained via previous RTI competitions, that are now in dire need of upgrade and replacement to continue the program. Our current focus is collaborative perception: the need for reliable, resilient and safe perception is a core challenge of autonomous robotics. One of the core perception algorithm in robotics is Simultaneous Localization And Mapping, or SLAM. Situational awareness, as provided by SLAM, is essential to most robotic systems. While it can be done on each robot individually, it is often beneficial to perform it collaboratively when working with groups of robots. In Collaborative SLAM, or C-SLAM, each individual robot performs single-robot SLAM, then communicates and performs data association with the other robots in order to build a common global map between them. This way, they can share a common reference frame for localization and a mutual understanding of the environment for decision-making. Our general objective is to reduce the rate of failures of multi-robot localization and mapping algorithms deployed in unknown and uncontrolled environments. We request a set of 20 AgileX Limo: a small but capable robot featuring a powerful onboard computer, a 3D camera, an inertial unit, and a lidar. Having at least 20 robots would allow us to experiment hierarchical swarms, collaborative transport, energy sufficiency, and collaborative SLAM. We also request 2 Bunker Mini robots to support our research on multi-robot exploration and mapping of GPS-denied environments. Our research output will be tested in collaboration with the European Space Agency (ESA), the Canadian Space Agency (CSA), and NASA JPL. Over the next five years, we expect 6 Postdoctoral fellows, 10 PhDs, 8 Master's and 15 undergraduates from the applicant's laboratory to be trained using this equipment.