PFI:BIC: iWork, a Modular Multi-Sensing Adaptive Robot-Based Service for Vocational Assessment, Personalized Worker Training and Rehabilitation, UT Arlington, Jan 2016 - Present
Automation, foreign competition, and the increasing use of robots replacing human jobs, stress the need for a major shift in vocational training practices to training for intelligent manufacturing environments, so-called "Industry 4.0". In particular, vocational safety training using the latest robot and other technologies is imperative, as thousands of workers lose their job or die on the job each year due to accidents, unforeseen injuries, and lack of appropriate assessment and training. The objective of this project is to build a smart robot-based vocational assessment and intervention system to assess the physical, cognitive and collaboration skills of an industry worker while he/she performs a manufacturing tasks in a simulated industry setting and collaborating with a robot to do a task. Data collected and analyzed come from sensors, wearables, and explicit user feedback measuring worker movements, eye gazes, errors made, performance delays, human-robot interactions, physiological metrics, and others, depending on the task.