外观
论文arXiv 2610.1227620 天前
迈向月球腿式机器人：LUNA现场部署经验
原文链接：Toward Lunar Legged Robots: Field Deployment Lessons at LUNA（arXiv 2610.12276 · 发布日期：2026-10-08）
Toward Lunar Legged Robots: Field Deployment Lessons at LUNA
面向月面腿式机器人部署不确定性，论文通过2025年LUNA模拟测试，总结其在月壤模拟物与类陨坑地形上的行走和感知经验。
核心要点
- 腿式机器人适合陡峭、松散、障碍丰富月面，但足-月壤、粉尘、光照感知等仍不确定。
- 在2025年LUNA类比活动中，ANYmal-D与Magnecko穿越松散月壤模拟物和类陨坑地形。
- 机器人可穿越月壤模拟物，但沉陷、打滑、扬尘接触及过曝、阴影、低纹理会影响表现。
- 结果推动月壤感知运动策略、抗光照感知、可重复类比测试和任务级运行验证的紧密集成。
验证范围与局限：验证范围为2025年LUNA类比场地中的松散月壤模拟物、类陨坑地形和挑战光照下的数据采集。
英文摘要 (Abstract)
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.
作者：Adrian Fuhrer, Joseph Church, Oliver Fischer, William Talbot, Nicolas Faesch, Yannic Hofmann, Hendrik Kolvenbach, Yusuke Tanaka, Marco Hutter
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