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Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders (LEARNER) - Human-Centered Intelligent Training for Emergency Responders
SessionT1 - Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders (LEARNER) - Human-Centered Intelligent Training for Emergency Responders
DescriptionEmergency response (ER) workers perform extremely demanding physical and cognitive tasks resulting in serious injuries and loss of life. Human augmentation technologies have the potential to enhance physical and cognitive work-capacities, thereby helping reduce injury risk, improving emergency response performance, as well as helping attract and retain skilled ER workers. This opportunity has been significantly hindered by the lack of high-quality training for ER workers that effectively integrates innovative and intelligent augmentation solutions. In this context, this panel presents the research considerations in the design and integration of use-inspired exoskeletons and augmented reality technologies in ER processes and the identification of unique cognitive and motor learning needs of each of these technologies in context-independent and ER-relevant scenarios. We propose a human-centered artificial intelligence (AI) enabled training framework for these technologies in ER, delivered across tiered access levels, covering the range of virtual, to mixed, to physical reality environments.
Boeing Technical Fellow - Human Factors and Ergonomics