Lidar导航实现月球车自动运货，精度达厘米级。
Lunar Rover Cargo Transport: Mission Concept and Field Test
- 用激光雷达教学-重复技术构建安全路径网络
- 实测在恶劣环境下完成吨级货物自主搬运与对接
- 适合月面探测与自动化运输系统研发者参考
未来月面任务中，自动驾驶车辆需在已知地点间运输货物。这些车辆必须能在安全区域精确导航，避开自然障碍、人工设施及危险阴影。月球车需将载荷自主停放在小公差范围内，以实现成功装卸。本实验采用激光雷达教学-重复方法，部署一吨级路径飞行验证车，在加拿大航天局类月地形场进行为期两周的实地测试。车辆以半自主远程控制模式绘制安全路径网络；路径学习完成后，可立即自主重复整个路径并携带货物运行。闭环性能足够精准，可对准载荷并完成抓取。本报告描述了模拟月面作业的最终测试，证实系统在严苛环境下的货物收集与交付能力。
原文摘要 · Abstract (English)
In future operations on the lunar surface, automated vehicles will be required to transport cargo between known locations. Such vehicles must be able to navigate precisely in safe regions to avoid natural hazards, human-constructed infrastructure, and dangerous dark shadows. Rovers must be able to park their cargo autonomously within a small tolerance to achieve a successful pickup and delivery. In this field test, Lidar Teach and Repeat provides an ideal autonomy solution for transporting cargo in this way. A one-tonne path-to-flight rover was driven in a semi-autonomous remote-control mode to create a network of safe paths. Once the route was taught, the rover immediately repeated the entire network of paths autonomously while carrying cargo. The closed-loop performance is accurate enough to align the vehicle to the cargo and pick it up. This field report describes a two-week deployment at the Canadian Space Agency's Analogue Terrain, culminating in a simulated lunar operation to evaluate the system's capabilities. Successful cargo collection and delivery were demonstrated in harsh environmental conditions.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。