van der Meer D, Chovet L, Bera A, Richard A, Sánchez Cuevas Pedro Jesus, Sánchez-Ibáñez J R, Olivares-Mendez M
Space Robotics (SpaceR) Research Group, Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg City, Luxembourg.
Advanced Centre for Aerospace Technologies (CATEC), Seville, Spain.
Front Robot AI. 2023 Mar 30;10:1127496. doi: 10.3389/frobt.2023.1127496. eCollection 2023.
Space resource utilisation is opening a new space era. The scientific proof of the presence of water ice on the south pole of the Moon, the recent advances in oxygen extraction from lunar regolith, and its use as a material to build shelters are positioning the Moon, again, at the centre of important space programs. These worldwide programs, led by ARTEMIS, expect robotics to be the disrupting technology enabling humankind's next giant leap. However, Moon robots require a high level of autonomy to perform lunar exploration tasks more efficiently without being constantly controlled from Earth. Furthermore, having more than one robotic system will increase the resilience and robustness of the global system, improving its success rate, as well as providing additional redundancy. This paper introduces the Resilient Exploration and Lunar Mapping System, developed with a scalable architecture for semi-autonomous lunar mapping It leverages Visual Simultaneous Localization and Mapping techniques on multiple rovers to map large lunar environments. Several resilience mechanisms are implemented, such as two-agent redundancy, delay invariant communications, a multi-master architecture different control modes. This study presents the experimental results of REALMS with two robots and its potential to be scaled to a larger number of robots, increasing the map coverage and system redundancy. The system's performance is verified and validated in a lunar analogue facility, and a larger lunar environment during the European Space Agency (ESA)-European Space Resources Innovation Centre Space Resources Challenge. The results of the different experiments show the efficiency of REALMS and the benefits of using semi-autonomous systems.
空间资源利用正在开启一个新的太空时代。月球南极存在水冰的科学证据、近期从月球风化层提取氧气的进展以及将其用作建造庇护所的材料,再次将月球置于重要太空计划的中心位置。这些由“阿耳忒弥斯”计划引领的全球项目,期望机器人技术成为推动人类实现下一次巨大飞跃的颠覆性技术。然而,月球机器人需要高度的自主性,以便在无需持续从地球进行控制的情况下更高效地执行月球探测任务。此外,拥有多个机器人系统将提高全球系统的弹性和稳健性,提高其成功率,并提供额外的冗余性。本文介绍了弹性探索与月球测绘系统,该系统采用可扩展架构开发,用于半自主月球测绘。它利用多辆漫游车的视觉同步定位与测绘技术来绘制大型月球环境地图。实施了多种弹性机制,如双智能体冗余、延迟不变通信、多主架构和不同控制模式。本研究展示了使用两个机器人的REALMS实验结果及其扩展到更多机器人数量的潜力,这将增加地图覆盖范围和系统冗余性。该系统的性能在月球模拟设施以及欧洲航天局(ESA)-欧洲空间资源创新中心空间资源挑战赛期间的更大月球环境中得到了验证和确认。不同实验的结果显示了REALMS的效率以及使用半自主系统的益处。