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Grant: Collaborative Research and Development Grants

University of Manitoba

$80,790.00

Specialized localization interface technologies for industrial robotic inspection

EF 2017-18

Résumé
Industrial inspection robot use is booming, e.g., in oil and gas wells, for inspections from a safe, remote location. Although robot technology is maturing, human-machine interfaces are limited, often having only raw video feeds and simple joysticks to remotely control a robot. Improved interface technologies are needed to support operator awareness of remote robots within environments, to improve operation performance. Through this project we will invent and prototype next-generation robotic interfaces, providing operators with intuitive access to cutting edge robot localization technologies and algorithms. While robot localization - the knowledge of where a robot is within an environment - is an established research area, there is little work on how this technology can be used by non-expert robot operators. E.g., maps can be difficult to interpret, crucial details for real-world use is often omitted (e.g., uncertainty, error) and operators cannot provide input at run time (e.g., to mark an error). Further, industrial partner Inuktun Services Ltd. has indicated that existing packages do not work with their environments, e.g., robots in pipe networks or attached to boat hulls, where global features, common edges such as walls, corners, and doors, are missing. Our team expertise includes human-robot interaction and interface design (Dr. Young), human perception (Dr. Bruce), deep learning (Dr. Wang), and computer vision (Drs. Bruce, Wang) expertise, which will provide HQP with multi-disciplinary training in employable areas including robotics, computer vision, and interface design. We will prototype and evaluate novel localization interfaces and algorithms for practical industrial inspection robots. We will research interfaces to help operators interpret output from, and provide input to, localization software, and novel algorithms that provide sufficient uncertainty data, receive operator input, and work in our inspection scenario. As the Canadian robotics industry continues to emerge on the international scale, this project positions Inuktun Services Ltd. to be a leader in establishing Canada as an important player in next-generation robotic control interfaces.
Programme
Collaborative Research and Development Grants
Emplacement
Manitoba, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
499663-2016
Name nom
Young, James
Department département
Computer Science
Organization id
19
Institution établissement
University of Manitoba
Province en
Manitoba
Province fr
Manitoba
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2016
Award amount
80790
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
2710
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information systems design
Research subject fr
Conception de systèmes d'information
Partie
2
Nb partie
2
Application title
Specialized localization interface technologies for industrial robotic inspection
Keyword
NSERC
Application summary
Industrial inspection robot use is booming, e.g., in oil and gas wells, for inspections from a safe, remote location. Although robot technology is maturing, human-machine interfaces are limited, often having only raw video feeds and simple joysticks to remotely control a robot. Improved interface technologies are needed to support operator awareness of remote robots within environments, to improve operation performance. Through this project we will invent and prototype next-generation robotic interfaces, providing operators with intuitive access to cutting edge robot localization technologies and algorithms. While robot localization - the knowledge of where a robot is within an environment - is an established research area, there is little work on how this technology can be used by non-expert robot operators. E.g., maps can be difficult to interpret, crucial details for real-world use is often omitted (e.g., uncertainty, error) and operators cannot provide input at run time (e.g., to mark an error). Further, industrial partner Inuktun Services Ltd. has indicated that existing packages do not work with their environments, e.g., robots in pipe networks or attached to boat hulls, where global features, common edges such as walls, corners, and doors, are missing. Our team expertise includes human-robot interaction and interface design (Dr. Young), human perception (Dr. Bruce), deep learning (Dr. Wang), and computer vision (Drs. Bruce, Wang) expertise, which will provide HQP with multi-disciplinary training in employable areas including robotics, computer vision, and interface design. We will prototype and evaluate novel localization interfaces and algorithms for practical industrial inspection robots. We will research interfaces to help operators interpret output from, and provide input to, localization software, and novel algorithms that provide sufficient uncertainty data, receive operator input, and work in our inspection scenario. As the Canadian robotics industry continues to emerge on the international scale, this project positions Inuktun Services Ltd. to be a leader in establishing Canada as an important player in next-generation robotic control interfaces.