Grant: Alliance Grants
Université du Québec en Outaouais
$45,000.00
Multi-UAV Active Simultaneous Localization and Mapping in Unknown Indoor Environments
FY 2022-23
Summary
Nowadays, unmanned aerial vehicles (UAVs) (also known as drones) are becoming crucial in countless applications. However, most of the traditional commercial drones are remotely piloted or semi-autonomous which places obstacles in the way of their efficient deployment in challenging conditions and time-critical missions (e.g., search and rescue). Fortunately, with the unceasing development of lightweight sensing and sophisticated real-time computing, drones can now be designed to self-perceive and make autonomous decisions during the execution of tasks. Yet, the next generation of UAVs will be living up to the hype only if we are able to successfully and efficiently deploy fleets of fully autonomous UAVs to accomplish even more complex missions and tasks. In fact, multiple drones can be deployed to speed up complex missions while collaboratively mapping and exploring an unknown environment. Collaboration not only accelerates the mapping and exploration process but also minimizes uncertainty in decision making. This research project aims at addressing several challenges related to the design of efficient and reliable localization, mapping, and exploration algorithms for multi-UAV systems navigating in unknown indoor environments. In particular, the challenge consists in deploying a fleet of UAVs, relaying on vision and inertial systems and endowed with limited on-board computational power, to autonomously navigate and map a completely unknown environment as fast and efficiently as possible. Our proposed solution for this technology challenge consists in the amalgamation of different approaches in control systems and robotics at different levels to coordinate the group of UAVs to accomplish this mission. The accomplishment of the research goals outlined in this project will open doors to new and exciting applications for fully autonomous multi-UAV systems operating in tangled environments. This project is also an excellent opportunity to train highly qualified professionals in these promising fields who can become leaders in research and technology, sustaining Canada's economic growth.
Program
Alliance Grants
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
576966-2022
Name nom
Berkane, Soulaimane S
Department département
Informatique et d'ingénierie
Organization id
54
Institution établissement
Université du Québec en Outaouais
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
45000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
703
Area of application group en
Transportation systems and services
Area of application group fr
Services et systèmes de transport
Area of application en
Aerospace
Area of application fr
Aérospatial
Research subject code
2601
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Robotic control
Research subject fr
Systèmes de commande
Installment
inst:1
Partie
1
Nb partie
1
Application title
Multi-UAV Active Simultaneous Localization and Mapping in Unknown Indoor Environments
Application summary
Nowadays, unmanned aerial vehicles (UAVs) (also known as drones) are becoming crucial in countless applications. However, most of the traditional commercial drones are remotely piloted or semi-autonomous which places obstacles in the way of their efficient deployment in challenging conditions and time-critical missions (e.g., search and rescue). Fortunately, with the unceasing development of lightweight sensing and sophisticated real-time computing, drones can now be designed to self-perceive and make autonomous decisions during the execution of tasks. Yet, the next generation of UAVs will be living up to the hype only if we are able to successfully and efficiently deploy fleets of fully autonomous UAVs to accomplish even more complex missions and tasks. In fact, multiple drones can be deployed to speed up complex missions while collaboratively mapping and exploring an unknown environment. Collaboration not only accelerates the mapping and exploration process but also minimizes uncertainty in decision making. This research project aims at addressing several challenges related to the design of efficient and reliable localization, mapping, and exploration algorithms for multi-UAV systems navigating in unknown indoor environments. In particular, the challenge consists in deploying a fleet of UAVs, relaying on vision and inertial systems and endowed with limited on-board computational power, to autonomously navigate and map a completely unknown environment as fast and efficiently as possible. Our proposed solution for this technology challenge consists in the amalgamation of different approaches in control systems and robotics at different levels to coordinate the group of UAVs to accomplish this mission. The accomplishment of the research goals outlined in this project will open doors to new and exciting applications for fully autonomous multi-UAV systems operating in tangled environments. This project is also an excellent opportunity to train highly qualified professionals in these promising fields who can become leaders in research and technology, sustaining Canada's economic growth.