Center/Site: iPerform Center for Assistive Technologies to Enhance Human Performance
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Center/Site Director: Dr. Fillia Makedon / Type: New
Project Leader: Fillia Makedon, UTA / Proposed Budget: $70/year, for 2 years
Project Description:
TITLE: iWork: A Smart Service for Vocational Assessment and Personalized Training and Rehabilitation
We propose to develop a smart vocational assessment and intervention service system, called iWork, that assesses a worker’s needs for training and rehabilitation in an experimental setup that simulates a factory. The system collects and analyzes multisensing human-robot interaction data and recommends personalized interventions that can improve the individuals for a particular job.
Experimental plan:
We use a simulation of an industrial setting, involving assembly of parts that mimics a manufacturing task and use this simulation to assess mental, cognitive, physical and robot collaboration capabilities of a worker.
Our system is capable of developing a variety of manufacturing task simulations that also address specific job requirements in industry. Our computational methods provide accurate assessments that can be used to prescribe targeted vocational training and/or rehabilitation suggestions to the experts.
Related work elsewhere:
Traditional Vocational Rehabilitation (VocRehab) addresses the needs of working-age adults who suffer from cognitive or mental issues and are in need of training. Moreover, research in human robot interaction and collaboration investigates how people want to interact with machines, towards a common goal.
There is currently no existing automated method to assess a human worker’s capabilities of collaborating with a robot, in an intelligent manufacturing environment, both implicitly and explicitly. In particular, there is no existing system that can be used to design a personalized intervention for a person looking for a manufacturing job or wishing to retain his/her job.
How this project is different:
While empirical research has been done to identify effective practices for VocRehab for people seeking a particular position in industry, none that we know of provides the immersive technological setting needed to train or even detect such deficiencies, as we propose to do, neither is it possible to collect results that can be duplicated.
Milestones for the current proposed year:
This service can be developed in collaboration with industry experts that wish to customize the iWork service to a particular industrial setting. Our goal is to build a prototype service, integrating assessment and training using task simulations, in collaboration with center partners. The outcomes of the proposed smart service can lead to huge commercial benefits for an industrial partner of iPerform.
Deliverables for the current proposed year:
The project deliverables include: An integrated multisensing assessment and training system; a set of task simulations that mimic industrial settings; a multisensing dataset; tools for behavioral analysis and extraction of patterns; tools for recommending personalized intervention.
How the project may betransformative and/or benefit society:
It will enable millions of workers to train appropriately in working with robots for Industry 4.0. The project will lead to job creation, job retraining, job retention and ensure on the job safety and accident reduction.
Research areas of expertise needed for project success:
Human Computer Interaction, Human Robot Interaction, Machine Learning, Data Mining, user interface design and analysis.
Potential Member Company Benefits:
This is a really needed smart service by companies and especially heavy industries. The system modular, expandable, relatively low cost, and personalizable. A company that adopts this system could easily commercialize and adopt it to a particular domain of products. As a service, iWork promises to provide targeted training that saves time and money.
Progress to Date:
Enabling methods and tools are in place, as well as a preliminary prototype of human robot interaction assessment.
Estimated Start Date: Septemer 1, 2017 / Estimated Knowledge Transfer Date: August 30, 2019
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