Do Earth-Trained Humanoid Controllers Walk on the Moon? Gravity, Terrain, and Soil Transfer
Year: 2026
Type: preprint
Abstract: Humanoid robots could aid lunar operations, but how to train their locomotion controllers for lunar gravity, terrain, and soil is unclear. We compare 12 strategies for a simulated Unitree G1 across gravity, terrain, and rigid or granular 3D resistive force theory (3D RFT) contact. Earth-trained policies keep 0.64 to 0.75 survival at the Moon on flat rigid ground in 10 s episodes, but falls continue, so longer episodes would see lower survival. Moon-trained and fine-tuned policies, in contrast, fall in every Earth episode, nearly all within 2 s. Rough-terrain training helps on uneven rigid ground only at training gravity. 3D RFT soil training helps on Earth sand but little on lunar soil. On three held-out soil models, Moon-trained policies lose no detectable progress at lunar gravity. Among tested strategies, only gravity-randomized rough 3D RFT training keeps mean survival above 0.83 at Earth and 0.95 at the Moon on all key tests up to 20 deg. Its ablation without soil training differs consistently only on soil at Earth gravity, falling in most sand episodes. These predictions depend on the contact model and soil stiffness, so lunar soil claims require agreement across soil models.
Source: arXiv (Cornell University)
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7223251149