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FAIR

FAIR project - Fatigue and ergonomics perception for human-care Intelligent collaborative Robot

Motivation

Work-Related Musculoskeletal Disorders (WRMSDs) are one of the major concerns of Industry 5.0(I5.0), representing 53% of occupational diseases, with annual costs of €240B. Serious WRMSDs risk factors are fatigue and awkward postures. Global trend is to equip manufacturing industries with collaborative robots (cobots). To successfully minimize WRMSDs risk, cobots should have a perception of Human physiological and ergonomic factors (Human-awareness) and cognitive skills to timely adapt their supportive collaboration to worker-specific needs (Human-care).

Goal

FAIR aims the development of a digital technology capable of adapting industrial tasks to the worker, for a healthy and collaborative operator 5.0. As an exploratory project, FAIR focuses on the continuous, holistic perception of the worker’s needs through representative Human factors, and the development of core control technology to timely-adapt the cobot assistance accordingly during real-industry task scenarios.  

Approach

FAIR proposes kinematics-based tools for a continuous assessment of workers’ fatigue indicators(level/onset) and postural ergonomics, measured by team-owned smart garments. FAIR advances towards truly adaptive human-robot collaboration. It develops two stand-alone controllers to adjust cobot motion to counteract the short-(posture) and long-term(fatigue) MSK burden while performing industrial tasks. Fatigue-driven controller adapts cobot motion as a direct function of an individual’s fatigue indicator. RULA-based kinematic indicator provides ergonomic assessment to adapt robot motion accordingly. A comprehensive adaptive impedance controller adjusts its parameters to timely change the robot position to enable to rest fatigated muscles and/or avoid awkward postures.

Impact

The outcomes include pilot demos of Human- and task-centred cobots and software modules for fatigue estimation with high transference potential to other interdisciplinary domains such as healthcare. Such advances will reduce number of WRMSDs, promoting Human well-being, and boost companies’ competitiveness through inclusive, productive, healthier workplaces, aligned with 3rd,8th,9th SDG of 2030 Agenda and European Innovation Capacity. FAIR’s impact is transversal to all industries with human-robot collaboration.

Team

FAIR is supported by a multidisciplinary and international consortium, teaming up robotic, biomedical, statistics, neurophysiology, electronic experts, and ergonomists. It includes members from University of Minho, University of Stuttgart, and Bosch Car Multimédia Portugal, S.A.

Grant

This project was funded by national funds through FCT- Fundação para a Ciência e Tecnologia, I.P., under the grant 2022.05844.PTDC.