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Human-Robot Team Vulnerabilities under Fatigue during sUAS Disaster Response Simulations

Ranjana K. Mehta, Aakash Yadav, Robin R. Murphy, S. Camille Peres

Year
2024
Citations
2

Abstract

Small uncrewed aerial systems (sUAS) play an important role in disaster response, assisting emergency responders in tasks such as search and rescue, damage assessment, and recovery. However, the prolonged and often unpredictable nature of disaster response operations can lead to elevated fatigue levels among sUAS pilots, causing increased errors and compromised mission effectiveness and safety. This study investigated the impact of fatigue on human-robot team (HRT) vulnerabilities during naturalistic sUA<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S$</tex> disaster response missions. Eighteen experienced sUA<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S$</tex> pilots participated in an overnight exercise replicating recent disaster response operational tempos including Hurricane Ian in 2023. Fatigue was assessed using objective and subjective measures, while researchers recorded predefined human-robot team (HRT) behaviors across mission phases. Results revealed increased fatigue over time, with varying impacts on HRT behaviors depending on the mission phase (initiation, execution, and termination) and crew role (pilot vs. visual observer). Pilots exhibited increased confusion and question-asking during mission initiation, compensatory strategies to maintain focus during execution, and more mistakes during termination as fatigue increased. Visual observers showed greater distraction but less confusion with fatigue during initiation, and task disengagement during execution. Findings highlight the need for targeted countermeasures to enhance sUA<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S$</tex> team effectiveness and safety during extended disaster response operations.

Keywords

Disaster responseEmergency responseHuman–robot interactionRobotComputer scienceEmergency managementArtificial intelligenceMedical emergencyMedicine

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