Grant: Discovery Grants Program - Individual
Toronto Metropolitan University
$27,000.00
Advanced Optical Sensing for Aerospace Guidance, Navigation and Control
EF 2022-23
Résumé
Aerospace vehicles frequently rely on optical sensors to determine system state. These instruments provide the direct external measurements necessary for a range of autonomous competencies. Attitude estimation, orbit determination, geolocation, relative maneuvering and obstacle avoidance all improve as their underlying sensing capabilities improve. This proposal examines how recent advances in the design of optical sensors can be leveraged to dramatically improve capabilities for guidance, navigation and control (GNC). A number of emerging optical technologies hold significant promise for high performance aerospace GNC applications. Plenoptic cameras, multispectral sensors, high-frame-rate imaging, and machine learning have seen significant innovation over recent years. Evaluated for their potential application in four key areas - i.e., spacecraft GNC, mobile robotics, adverse imaging, and calibration and production - these technologies will enable new types of missions for both planetary rovers and orbiting spacecraft. Technological innovations benefit GNC sensors in several ways. Improving measurement accuracy and reducing noise and bias are obvious pathways to enhanced performance. However, other high level metrics can be just as important. Higher sensor update rates provide a more complete description of vehicle motion. Improving sensor availability, i.e., the tolerance to adverse circumstances such as motion, noise, lighting, etc., can increase system robustness and the quality of the derived navigation solution. These three performance metrics will define the framework used in this research program for evaluating new technologies. Although seemingly disparate, the technologies highlighted in this proposal illustrate how advances in camera design and image processing can greatly enhance the performance of the optical sensors found on many aerospace vehicles. These innovations, driven by terrestrial machine vision applications, are nonetheless powerful enablers of the technical capabilities currently the focus of aerospace GNC research. As the capabilities of these systems grow the larger benefits to society, from industrial automation to natural resources management, are vast and growing.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2022-03815
Name nom
Enright, John
Department département
Aerospace Engineering - Aerospace Engineering
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
27000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
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
2100
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Mechanical engineering
Research subject fr
Génie mécanique
Installment
inst:1
Partie
1
Nb partie
5
Application title
Advanced Optical Sensing for Aerospace Guidance, Navigation and Control
Application summary
Aerospace vehicles frequently rely on optical sensors to determine system state. These instruments provide the direct external measurements necessary for a range of autonomous competencies. Attitude estimation, orbit determination, geolocation, relative maneuvering and obstacle avoidance all improve as their underlying sensing capabilities improve. This proposal examines how recent advances in the design of optical sensors can be leveraged to dramatically improve capabilities for guidance, navigation and control (GNC). A number of emerging optical technologies hold significant promise for high performance aerospace GNC applications. Plenoptic cameras, multispectral sensors, high-frame-rate imaging, and machine learning have seen significant innovation over recent years. Evaluated for their potential application in four key areas - i.e., spacecraft GNC, mobile robotics, adverse imaging, and calibration and production - these technologies will enable new types of missions for both planetary rovers and orbiting spacecraft. Technological innovations benefit GNC sensors in several ways. Improving measurement accuracy and reducing noise and bias are obvious pathways to enhanced performance. However, other high level metrics can be just as important. Higher sensor update rates provide a more complete description of vehicle motion. Improving sensor availability, i.e., the tolerance to adverse circumstances such as motion, noise, lighting, etc., can increase system robustness and the quality of the derived navigation solution. These three performance metrics will define the framework used in this research program for evaluating new technologies. Although seemingly disparate, the technologies highlighted in this proposal illustrate how advances in camera design and image processing can greatly enhance the performance of the optical sensors found on many aerospace vehicles. These innovations, driven by terrestrial machine vision applications, are nonetheless powerful enablers of the technical capabilities currently the focus of aerospace GNC research. As the capabilities of these systems grow the larger benefits to society, from industrial automation to natural resources management, are vast and growing.