Mind the ARm: realtime visualization of robot motion intent in head-mounted augmented reality

Abstract

Established safety sensor technology shuts down industrial robots when a collision is detected, causing preventable loss of productivity. To minimize downtime, we implemented three Augmented Reality (AR) visualizations (Path, Preview, and Volume) which allow humans to understand robot motion intent and give way to the robot. We compare the different visualizations in a user study in which a small cognitive task is performed in a shared workspace. We found that Preview and Path required significantly longer head rotations to perceive robot motion intent. Volume, however, required the shortest head rotation and was perceived as most safe, enabling closer proximity of the robot arm before one left the shared workspace without causing shutdowns.