March 14, 2024

Energy-Aware Hierarchical Markets for Autonomous Lunar Construction

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 (v0.2.0) and executed in Leviathan (py-0.2.0) with energy fields, the upgraded communication model, and OpenMP-parallel physics. Micro swarms locally optimize excavation and compaction; macro fleets allocate hauling/printing tasks via decentralized auctions respecting state-of-charge (SOC), wear, and thermal constraints. We compare against (i) first-come-first-serve (FCFS) and (ii) a genuine MILP central planner built on OR-Tools with a fixed 60-second wall-clock budget per replan and a 30-second replan cadence — sized to be a credible centralized comparator, not a strawman. Across lunar-base construction scenarios HMA increased mobility-energy-only throughput by 31% and reduced idle time by 44% versus FCFS, and matched the MILP planner on throughput within 4% while tolerating failures the planner cannot. Under 10% micro mortality and 5% macro downtime HMA sustained ≥87% throughput with task reallocation latencies under 12 s. We add a queueing-theoretic decoupling argument (Little's Law plus M/M/c at each depot) showing that buffer size $B^* = \rho^2/(c(1-\rho))$ achieves stable macro–micro decoupling, matching the empirical knee in the buffer-size sweep. We also explicitly scope our energy numbers: $\varepsilon = 58.5$ Wh/kg is mobility-only energy; sintering thermodynamics (~1–5 MJ/kg) are accounted for separately at printers and reported in §5.6. The previous draft's apparent throughput of 3,250 kg/h exceeded the 3,000 kg/h micro-production ceiling — the corrected number, derived directly from experiment.json, is 2,915 kg/h. We reconcile the two utility-function specifications used in earlier drafts (§3.2 hinge vs Appendix A sigmoid) into a single canonical form. Maneuver.Map orchestrations reveal stable macro–micro interfaces: buffer depots decouple rates and role rotation avoids energy death spirals.

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Read the full paper on arXiv