LUNARMINERS: Lunar Mining for Water-Ice Etraction by Implementing Nature-Inspired Behavior in Robotic Swarms

This paper introduces LUNARMINERS framework and applies it for lunar water-ice extraction in Shackleton Crater at the lunar South Pole. The LUNARMINERS combines artificial intelligence swarm robotics with biomimetic swarm behavior. In the proposed framework, the foraging behavior of ants, the light attraction behavior of fireflies, and the migratory flight strategy of wild geese have been comprehensively analyzed and applied to robotic swarms for lunar mining. This research takes into consideration important aspects of the lunar environment, such as permanently shadowed regions (PSRs) and communication limitations in lunar craters, by simulating them in Robot Operating System (ROS). The LUNARMINERS framework has advantages over other methods in that it allows for the survey of an area of 0.025 km2 per day while achieving 100% water-ice deposition effectiveness. Studies show that by applying the LUNARMINER framework, the exploration of the entire Shackleton Crater can be completed in 3.75 Earth years via 15 robots. Simulations of the implementation of the proposed LUNARMINERS framework have demonstrated reliable high-levels of extraction efficiency, with the framework producing 12.9 metric tons of water-ice per day, which potentially can support up to 1,990 people per day based on astronaut’s daily water requirements from NASAs Human Integrated Design Handbook (HIDH) and thus, establishing a sustainable benchmark for lunar habitation. The results from this study show that the advances in the proposed LUNARMINERS framework can contribute to future lunar exploration and ISRU, setting new standards for sustainable off-Earth mining.