Evaluation of the Human-Robot-Interaction Dynamic Under Mental Fatigue Constraints In Search and Rescue Operations

Human-robot applications that allow for work to be done remotely are largely dependent on the lassitude of the operators. The exhaustion of these operators is a result of work completion and duration. Existing literature focuses on measuring human fatigue in attempt to quantify the effect on the response. This paper explores the impact of a fatigued human on human-robot applications, particularly, search and rescue aided by a unmanned aerial vehicle (UAV) swarm. A model is presented that describes the relationship between the mental fatigue and responsiveness of the operator over extended periods of time. A simulation of the operation is conducted in which the operator is dependent upon the swarm surveying the area and generating reports. Operation efficiency is estimated according to the human-robot feedback loop, which if not managed, can negatively affect the dynamic. The analysis identifies a trade-off between swarm size and operator fatigue on operation timeliness. The results show that for an operator, there exists an optimal swarm size depending on their level of capability. A more capable operator fatigues at a slower rate and hence, can complete work at a faster rate. This paper details how to evaluate these systems so that operation costs and operator fatigue can be minimized.1