AI-Driven Swarm Intelligence for Autonomous Methane Plume Detection and Mapping on Titan's Cryogenic Surface

Staffieri C.; Staffieri F.; Staffieri A.; Gupta M.; Bett J.S.P.; Alzadjali B.; Bhagat A.; Fathy N. · Proceedings of the International Astronautical Congress, IAC (2025) · DOI: 10.52202/083076-0058

Resumen

This study proposes a new framework that leverages AI-powered swarm intelligence for autonomous discovery and high-fidelity mapping of methane plumes over Titan's cryovolcanic surface. Saturn's largest moon's extreme environment, characterized by low temperatures (180C), a thick atmosphere composed of nitrogen and methane, and complex organic chemistry, poses significant challenges for traditional robotic exploration. To counteract such obstacles, a distributed swarm composed of miniature, lowenergy consumption robots with tunable laser spectrometry and gas sensors for real-time measurement of methane concentration is proposed. The swarm operates under a hybrid decentralized-centralized scheme, in which individual agents use reinforcement algorithms for enhancing localized navigation and information collection with strong connectivity for supporting group decision-making processes. An event-triggered communications scheme reduces latency and bandwidth constraints, allowing for effective information dissemination even in Titan's challenging radio frequency environment. In addition, a multi-objective algorithm integrates sensor information fusion, path planning, and resource management for prioritization of regions of interest according to gradients in methane concentration and geologic signatures for presence of subsurface hydrocarbon reservoirs. Simulations conducted in a high-fidelity environment emulating Titan illustrate the swarm's ability to detect and map methane plumes with accuracy at a level below a kilometer, dynamically compensating for uncertain terrain and changing atmospheric dynamics. In addition, the system incorporates fault tolerance for assuring robustness in case of hardware failure or extreme weather events. Not only does this approach enhance scientific productivity, but it forms a basis for future in-situ resource utilization (ISRU) missions for exploiting Titan's rich hydrocarbon reserves. The suggested approach reflects a revolutionary development in planetary exploration, showcasing capabilities emerging through combining AI-powered swarm robotics with advanced sensing technology, with a view to shedding light on the mysteries of distant celestial bodies. Future studies will then focus on developing and testing the swarm platform in analog environments in order to evaluate its performance in real operational environments. Copyright

Instituciones: Universidad Nacional de Ingeniería