DeFatigue: Online Non-Intrusive Fatigue Detection by a Robot Co-Worker

A robot as a companion or co-worker is not an emerging concept anymore, but a reality. However, one of the major barriers to this realization is the seamless interaction with the robots that includes both explicit and implicit interaction. In this work, we assume a use-case where a human and a robot together carry a heavy object in a co-habitat (home or workplace/factory). Two human beings while doing such a work understands each other without explicit (vocal) interaction. To realize such behavior, the robot must understand the fatigue state of the human co-worker to enable seamless work experience and ensure safety. In this article, we present DeFatigue, a non-intrusive fatigue state detection mechanism. We assume that the robot's hand is equipped with a force sensor. Based on the change of force from the human side while carrying the object, DeFatigue is able to determine the fatigue state without instrumenting the human being with an additional sensor (internally or externally). Moreover, it detects the fatigues state on-the-fly (online) as well as it does not require any (user-specific) training. Based on our experiments with 18 test subjects, fatigue state detection by DeFatigue overlaps with the ground truth for 85.18% of the cases whereas it deviates 4.09 s (on average) for the remaining cases.