Miniature robot for mining lunar ice

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master_Kunowski_Grzegorz_2025.pdf (13.04 MB)

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School of Electrical Engineering | Master's thesis
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Date

2025-10-26

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Major/Subject

Space Robotics and Automation

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Degree programme

Master's Programme in Space Science and Technology
Master's Programme in Space Science and Technology
Master's Programme in Space Science and Technology

Language

en

Pages

111

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Abstract

Presently, the predominant approach to in-situ lunar ice extraction focuses on collecting and processing regolith near the South Pole, where the average ice content is approximately 4\%. While this method is well suited to current technological capabilities, it is expected to become increasingly inefficient for future large-scale lunar operations. This thesis presents an alternative strategy that employs multiple small rovers operating with swarm behaviour to excavate ice directly from lunar craters, thereby achieving significantly greater efficiency. The proposed rover, designed in SOLIDWORKS, is a legged hexapod emphasising mechatronic design. Detailed software, instrumentation, and electronic systems were excluded due to the scope of the thesis, but the concept was validated through ROS2 simulations. Despite numerous assumptions, the results strongly suggest that the proposed approach could be at least 100 times more efficient than existing methods. Under continuous operation, with allowances made for maintenance downtime, a fleet of 350 cooperative rovers completing 400 trips each within 15 Earth days could extract approximately 1,306 tonnes of ice. This figure represents more than 2,700 times the benchmark set by NASA’s Break the Ice Challenge. Although speculative in nature, the findings indicate considerable potential. It is therefore recommended that this approach and its design principles be investigated further for application in future lunar operations.

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Supervisor

Kiviluoma, Panu

Thesis advisor

Kallio, Esa

Keywords

robotics, mechatronics, lunar ice, ice excavation, mining ice, lunar operation

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https://urn.fi/URN:NBN:fi:aalto-202512159190

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