Real-Time Trust Dynamics in Space Cyber-Human Teaming

Cislune Inc., in collaboration with the University of Central Florida (UCF), proposes the development of an analytical framework designed to enhance the safety and efficacy of lunar missions by optimizing the interaction dynamics between astronauts and Autonomous Systems (AS). This initiative aims to refine decision-making processes through the advanced integration of state-of-the-art machine learning algorithms, data analytics, and uncertainty quantification (UQ) techniques, specifically focusing on improving trust dynamics in Cyber-Physical-Human (CPH) teams. The intended use of funding is to prototype and validate this framework, aiming for a 10% reduction in crew cognitive workload by enhancing the quality and representation of mission-critical data, such as breathable oxygen levels, propellant stores, and rover range. Utilizing immersive technologies like OpenMCT for data visualization and Cislune’s SimMoon for scenario simulations, the project targets the development of a proof of concept documented in a comprehensive Phase I final report. This framework is not only pivotal for the Artemis 3 mission, aiming to ensure astronaut safety and mission success through reliable and efficient decision-making but also sets the groundwork for broader applications in future lunar and deep space exploration missions. The target markets encompass NASA's lunar exploration initiatives and commercial space entities focused on establishing a sustained human presence on the Moon, offering a significant leap in the operational capabilities of CPH teams in space exploration contexts.