Abstract
We study coordinated operations between millimeter-scale micro swarms (regolith processing) and macro-scale robots (haulers, printers) for lunar in-situ resource utilization (ISRU). We propose a hierarchical market-based scheduler with energy-aware auctions (HMA), implemented in Gossamer and executed in Leviathan with energy fields, a range-limited communication model, and OpenMP-parallel physics. Micro swarms locally optimize excavation and compaction; macro fleets allocate hauling tasks via decentralized auctions in which a hauler's bid is the mass recovered per joule, gated by a state-of-charge sigmoid so that a depleted hauler withdraws from the market rather than stranding itself. We compare against (i) first-come-first-serve (FCFS) and (ii) a MILP central planner built on OR-Tools under a fixed per-replan time budget — a credible centralized comparator, and a deliberately harder test than the greedy baselines this literature usually adopts.
Our central finding is that the market's advantage is regime-dependent, and that the regime structure is the result. When hauler capacity is starved or over-provisioned the three schedulers converge and there is no allocation problem to solve; only in the contended middle does the choice of scheduler move throughput, where HMA raises printed mass by 29% over FCFS and 17% over the central planner and cuts per-kilogram mobility energy by roughly 20%. A single headline number would conceal this, and would mislead a fleet designer about when the machinery is worth its complexity.