Our new paper has been published: “Human-Aware Robot Behaviour in Self-Driving Labs”, https://dl.acm.org/doi/epdf/10.1145/3776734.3794402
Self-driving laboratories are transforming research in chemistry and materials science to accelerate new discoveries. Mobile robot chemists play a pivotal role by autonomously navigating the lab to transport samples, effectively connecting synthesis, analysis, and characterisation equipment. Here we present an initial study of an embodied, AI-driven perception method that facilitates proactive human-robot interaction in shared-access scenarios. Our method features a hierarchical human intention prediction model that allows the robot to distinguish between preparatory actions (waiting) and transient interactions (accessing the instrument). Our results demonstrate that the proposed approach enhances efficiency by enabling proactive human–robot interaction, streamlining coordination, and potentially increasing the efficiency of autonomous scientific labs.
Paper can be accessed here: https://dl.acm.org/doi/epdf/10.1145/3776734.3794402