This paper introduces FR-GESTURE, a novel RGBD dataset for gesture-based control of Unmanned Ground Vehicles (UGVs) by First Responders (FRs). It defines 12 specific gestures inspired by existing FR signals and tactical hand signals, collected to facilitate more intuitive human-robot interaction in disaster scenarios.

This paper proposes considering Theory of Mind (ToM) in Human-Robot Interaction (HRI) as a form of Explainable AI (XAI) and evaluates existing ToM studies using an XAI framework, identifying gaps in assessing explanation fidelity. It advocates for an integrated approach combining ToM's user focus with XAI's technical rigor.