Proposing Human-Robot Trust Assessment Through Tracking Physical Apprehension Signals in Close-Proximity Human-Robot Collaboration

We propose a method of human-robot trust assessment in close-proximity human-robot collaboration involving body tracking for recognition of physical signs of apprehension. We tested this by performing skeleton tracking on 30 participant while they repeated a shared task with a Sawyer robot while reporting trust between tasks. We tested different robot velocity and environment conditions with an unannounced increase in velocity midway through to provoke a dip trust. Initial analysis show significant effect for the test conditions on participant movements and reported trust as well as linear correlations between tracked signs of apprehension and reported trust.