Control of a Bucket-Wheel for Surface Mining of Asteroids and Small-Bodies (1702.00335v2)
Abstract: Near Earth Asteroids (NEAs) are thought to contain a wealth of resources, including water, iron, titanium, nickel, platinum and silicates. Future space missions that can exploit these resources by performing In-Situ Resource Utilization (ISRU) gain substantial benefit in terms of range, payload capacity and mission flexibility. Compared to the Moon or Mars, the milligravity on some asteroids demands a fraction of the energy for digging and accessing hydrated regolith just below the surface. However, asteroids and small-bodies, because of their low gravity present a major challenge in landing, surface excavation and resource capture. These challenges have resulted in adoption of a "touch and go techniques", like the upcoming Osiris-rex sample-return mission. Previous asteroid excavation efforts have focused on discrete capture events (an extension of sampling technology) or whole-asteroid capture and processing. This paper analyzes the control of a bucket-wheel design for asteroid or small-body excavation. Our study focuses on system design of two counter rotating bucket-wheels that are attached to a hovering spacecraft. Regolith is excavated and heated to 1000 C to extract water. The water in turn is electrolyzed to produce hydrogen and oxygen for rocket fuel. We analyze control techniques to maximize traction of the bucket-wheels on the asteroid surface and minimize lift-off the surface, together with methods to dig deeper into the asteroid surface. Our studies combine analytical models, with simulation and hardware testing. For initial evaluation of material-spacecraft dynamics and mechanics, we assume lunar-like regolith for bulk density, particle size and cohesion. Our early studies point towards a promising pathway towards refinement of this technology for demonstration aboard a future space mission.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.