Perturbation Detection in Space-based Human-Machine Teams (HMTs) in Different Layers

Abstract

This study focuses on detecting unique and complex challenges of Human-Machine Teaming (HMT) in space missions, where coordination among humans, robots, and AI agents is critical. Such missions are beset by “perturbations”—unexpected challenges involving communication delays due to the vast distances separating team elements. These issues must be overcome to maintain the safety and effectiveness of space-based missions. This study conducted engineering tests to evaluate the impact of perturbations on communication and vehicle operations and the physiological state of the humans involved. It outlines an experimental scenario involving various space entities (e.g., lunar colonies; orbiters; rovers) to simulate space mission conditions and communication and coordination challenges. The study employs layered dynamics methods to detect perturbations in technological and cognitive team states across the mission, using sensors and information entropy as key analytical tools.