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Grant: Alliance Grants

University of Victoria

$140,000.00

Counter-UAS: Interceptor drone "design, build, test and fly" with AI-enhanced situational awareness [C-UAS]

EF 2024-25

Résumé
The Department of National Defence - Department of Research and Development Canada (DND-DRDC) have requested a proposal on "intelligent, agile and low cost "interceptor" drones to seek and engage hostile, non-cooperative and non-compliant drones. The research program proposes the development of a holistic C-UAS program based on an effective interceptor drone equipped with AI-enhanced airborne decision-making and trajectory planning, and neutralization agents. The research team will design, develop, validate, and evaluate C-UAS solutions using multidisciplinary design optimization tools and processes and flight testing of interceptor drones with a range of >10 km that are able to defeat autonomous Class 1 RPAS (<150 kg). The interceptor drone will be equipped with sensors to augment situation awareness and AI-enhanced Guidance, Navigation, and Control (GNC) to engage and neutralize the target non-cooperative drone(s). The implementation of multi-agent flight formation will also be explored to increase the probability of a successful interception. The artificial intelligence methods and algorithms developed for intelligent unmanned aerial systems in this project will be designed to be readily deployable in real-world environments where safety and robustness are imperative. With the integration of uncertainty management methods into machine learning this project will introduce practical solutions for some of the most critical issues of this powerful modeling paradigm. These efforts will contribute to the operational readiness of the Canadian Armed Forces including combat and surveillance operations, but many other civil and commercial applications would benefit from this effort such as environmental monitoring, security, emergency response, and surveillance. Further, individual technology components of the proposed program such as 3D computer vision will create opportunities for innovation in academic and industrial research and development. The outcome of the project aims to assist DRDC in making informed decisions on the implementation of C-UAS strategies for national defence.
Programme
Alliance Grants
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
598630-2024
Name nom
Najjaran, Homayoun H
Department département
Mechanical Engineering
Organization id
7
Institution établissement
University of Victoria
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
140000
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
2100
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Mechanical engineering
Research subject fr
Génie mécanique
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Counter-UAS: Interceptor drone "design, build, test and fly" with AI-enhanced situational awareness [C-UAS]
Keywords
ai guidance, navigation, and control; counter-unmanned air systems; interceptor drones; multi-uas flight formation; sense and avoid
Application summary
The Department of National Defence - Department of Research and Development Canada (DND-DRDC) have requested a proposal on "intelligent, agile and low cost "interceptor" drones to seek and engage hostile, non-cooperative and non-compliant drones. The research program proposes the development of a holistic C-UAS program based on an effective interceptor drone equipped with AI-enhanced airborne decision-making and trajectory planning, and neutralization agents. The research team will design, develop, validate, and evaluate C-UAS solutions using multidisciplinary design optimization tools and processes and flight testing of interceptor drones with a range of >10 km that are able to defeat autonomous Class 1 RPAS (<150 kg). The interceptor drone will be equipped with sensors to augment situation awareness and AI-enhanced Guidance, Navigation, and Control (GNC) to engage and neutralize the target non-cooperative drone(s). The implementation of multi-agent flight formation will also be explored to increase the probability of a successful interception. The artificial intelligence methods and algorithms developed for intelligent unmanned aerial systems in this project will be designed to be readily deployable in real-world environments where safety and robustness are imperative. With the integration of uncertainty management methods into machine learning this project will introduce practical solutions for some of the most critical issues of this powerful modeling paradigm. These efforts will contribute to the operational readiness of the Canadian Armed Forces including combat and surveillance operations, but many other civil and commercial applications would benefit from this effort such as environmental monitoring, security, emergency response, and surveillance. Further, individual technology components of the proposed program such as 3D computer vision will create opportunities for innovation in academic and industrial research and development. The outcome of the project aims to assist DRDC in making informed decisions on the implementation of C-UAS strategies for national defence.