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2014 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) (2014)
Munich, Germany
Sept. 10, 2014 to Sept. 12, 2014
ISBN: 978-1-4799-6184-9
pp: 17-22
Zhiwei Zhu , SRI International, USA
Vlad Branzoi , SRI International, USA
Michael Wolverton , SRI International, USA
Glen Murray , SRI International, USA
Nicholas Vitovitch , SRI International, USA
Louise Yarnall , SRI International, USA
Girish Acharya , SRI International, USA
Supun Samarasekera , SRI International, USA
Rakesh Kumar , SRI International, USA
AR-Mentor is a wearable real time Augmented Reality (AR) mentoring system that is configured to assist in maintenance and repair tasks of complex machinery, such as vehicles, appliances, and industrial machinery. The system combines a wearable Optical-See-Through (OST) display device with high precision 6-Degree-Of-Freedom (DOF) pose tracking and a virtual personal assistant (VPA) with natural language, verbal conversational interaction, providing guidance to the user in the form of visual, audio and locational cues. The system is designed to be heads-up and hands-free allowing the user to freely move about the maintenance or training environment and receive globally aligned and context aware visual and audio instructions (animations, symbolic icons, text, multimedia content, speech). The user can interact with the system, ask questions and get clarifications and specific guidance for the task at hand. A pilot application with AR-Mentor was successfully built to instruct a novice to perform an advanced 33-step maintenance task on a training vehicle. The initial live training tests demonstrate that AR-Mentor is able to help and serve as an assistant to an instructor, freeing him/her to cover more students and to focus on higher-order teaching.
Vehicles, Training, Maintenance engineering, Visualization, Three-dimensional displays, Databases, Speech

Z. Zhu et al., "AR-mentor: Augmented reality based mentoring system," 2014 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Munich, Germany, 2014, pp. 17-22.
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