Grant: Research Tools and Instruments
École Polytechnique de Montréal
$126,235.00
Robotic Perception in Extreme Environments
FY 2020-21
Summary
Rapid advances in artificial intelligence are driving the adoption of robotics and automation in transport and logistics, providing new solutions to passenger transport, last-mile delivery, and automated warehouses. These systems carry a high level of risk to public safety and it is our duty as robotics engineers to design the safest possible systems.
Since environmental perception systems are essential to any autonomous robotic system it is imperative to avoid errors in these systems. This is all the more important in extreme environments (in challenging weather, underwater environments, caves, etc.), where sensors (cameras, sonars, etc.) are subject to high levels of noise and frequently produce erroneous measurements. Tragedies involving Lion Air's Boeing 737 Max and Tesla are sad examples of the consequences of erroneous sensor and perception systems failures. The mitigation of spurious measurements has been
studied in perceptual tasks such as the recording of point clouds required for remote sensing (i.e. using LiDAR) or the alignment of 3D shapes. There is an urgent public safety need to address these issues, especially with the emergence of transport and logistics robotic systems, such as autonomous flying or driving vehicles.
In this research program, we will address how to autonomously reduce the adverse effects of erroneous measurements on robotic perception systems in extreme environments. There is no comprehensive solution to perception failures in robotics, especially in presence of erroneous measurements, which could be a showstopper to the deployment of robots in society. With more robust perception, robots will be safer and will be able to venture into increasingly hostile environments. Eventually, provable robustness could lead to certifiable systems, which would allow their introduction in safety-critical applications. In particular, we are interested in rapid mapping, localization, and navigation in limited-access and communication-restricted areas (e.g. space exploration, mining, etc.), where perception failures could lead to material loss and danger to human life.
To achieve this goal we request a Boston Dynamics Spot, an all-terrain agile robot with an extensive sensor suite, that we plan to deploy in mapping missions in extreme environments such as caves and mountains in collaboration with space agencies in North America and Europe.
Program
Research Tools and Instruments
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RTI-2021-00770
Name nom
Beltrame, Giovanni
Department département
Computer and Software Engineering
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
2020
Competition year année de concours
2021
Award amount
126235
Program id
RTI
Program name en
Research Tools and Instruments
Program name fr
Outils et instruments de recherche
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1610
Committee name en
Electrical and Computer Engineering (RTI)
Committee name fr
Génie électrique et infomatique (OIR)
Area of application code
1204
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Space and astronomy
Area of application fr
Sciences spatiales et astronomie
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:1-1
Partie
1
Nb partie
1
Application title
Robotic Perception in Extreme Environments
Keyword
NSERC
Application summary
Rapid advances in artificial intelligence are driving the adoption of robotics and automation in transport and logistics, providing new solutions to passenger transport, last-mile delivery, and automated warehouses. These systems carry a high level of risk to public safety and it is our duty as robotics engineers to design the safest possible systems.
Since environmental perception systems are essential to any autonomous robotic system it is imperative to avoid errors in these systems. This is all the more important in extreme environments (in challenging weather, underwater environments, caves, etc.), where sensors (cameras, sonars, etc.) are subject to high levels of noise and frequently produce erroneous measurements. Tragedies involving Lion Air's Boeing 737 Max and Tesla are sad examples of the consequences of erroneous sensor and perception systems failures. The mitigation of spurious measurements has been
studied in perceptual tasks such as the recording of point clouds required for remote sensing (i.e. using LiDAR) or the alignment of 3D shapes. There is an urgent public safety need to address these issues, especially with the emergence of transport and logistics robotic systems, such as autonomous flying or driving vehicles.
In this research program, we will address how to autonomously reduce the adverse effects of erroneous measurements on robotic perception systems in extreme environments. There is no comprehensive solution to perception failures in robotics, especially in presence of erroneous measurements, which could be a showstopper to the deployment of robots in society. With more robust perception, robots will be safer and will be able to venture into increasingly hostile environments. Eventually, provable robustness could lead to certifiable systems, which would allow their introduction in safety-critical applications. In particular, we are interested in rapid mapping, localization, and navigation in limited-access and communication-restricted areas (e.g. space exploration, mining, etc.), where perception failures could lead to material loss and danger to human life.
To achieve this goal we request a Boston Dynamics Spot, an all-terrain agile robot with an extensive sensor suite, that we plan to deploy in mapping missions in extreme environments such as caves and mountains in collaboration with space agencies in North America and Europe.