发表机构
ETH Zurich; ESA/DLR LUNA lunar analogue facility（苏黎世联邦理工学院; 欧空局/德国航空航天中心LUNA月球模拟设施）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究基于2025年LUNA模拟任务，测试ANYmal-D和Magnecko在月壤模拟物等地形的表现，发现腿式机器人穿越性能受多种因素影响，为未来月球腿式机器人研发提供经验。
AI 中文摘要
腿式机器人是未来月球表面任务的有潜力候选者，因为它们能穿越陡峭、松散且障碍物密集的地形，而这类地形对传统轮式漫游车构成挑战。不过，月球部署的准备工作受限于足-月壤相互作用、粉尘产生、光照导致的感知退化以及操作约束等不确定性。本文报告了2025年LUNA模拟任务的经验教训，在该任务中，ANYmal-D和Magnecko机器人穿越了松散的月壤模拟物和陨石坑状地形，并在挑战性光照条件下收集了长距离导航及视觉-惯性数据。研究表明，四足机器人可穿越月壤模拟物，但性能受沉陷与滑移、产生粉尘的接触以及过曝、阴影和低纹理区域导致的感知故障影响。这些结果推动未来月球腿式机器人需更紧密整合感知月壤的运动策略、抗光照感知、可重复的模拟测试以及任务级操作验证。
英文摘要
Legged robots are promising candidates for future lunar surface missions because they can traverse steep, loose, and obstacle-rich terrain that challenges conventional wheeled rovers. However, readiness for lunar deployment is limited by uncertainties in foot-regolith interaction, dust generation, illumination-driven perception degradation, and operational constraints. This paper reports lessons from the 2025 LUNA analogue campaign, where ANYmal-D and Magnecko traversed loose regolith simulant and crater-like terrain and collected long-horizon navigation and visual-inertial data under challenging lighting. We show that quadrupedal robots can traverse regolith simulant, but performance is affected by sinkage and slip, dust-generating contacts, and perception failures caused by overexposure, shadows, and low-texture regions. These results motivate tighter integration of regolith-aware locomotion policies, illumination-robust perception, repeatable analogue testing, and mission-level operational validation for future lunar legged robots.
CommentsProceeding to the IEEE iSparo Conference 2026
