用于行星探测的四足机器人：在活火山上开展控制算法实地测试
Quadrupeds for Planetary Exploration: Field Testing Control Algorithms on an Active Volcano
AI总结：
为验证四足机器人行星探测相关算法，DFKI在AAPLE项目中于武尔卡诺活火山开展实地测试，验证了新型自适应最优控制算法在类月火地形中的有效性，介绍了测试的技术方案与结果。
摘要：
“机智号”直升机等任务已证明，采用新型运动模式可提升行星探测任务的科学回报。足式机器人能够穿越比轮式漫游车更难通行的地形，例如跳过地面裂缝或穿越布满巨石的崎岖地形，可进一步拓展未来行星任务的探测范围与能力。为开发并测试四足机器人相关算法，德国人工智能研究中心（DFKI）开展了AAPLE项目。作为项目的一部分，我们在意大利西西里岛附近的活层状火山——埃奥利群岛的武尔卡诺火山上开展了一系列实地实验。实验重点是在高保真的月球与火星表面模拟环境中，验证最新研发的四足运动自适应最优控制算法的性能。本文介绍了武尔卡诺火山实验活动的技术方案、测试计划、软件架构、实地部署策略及评估结果。
英文摘要：
Missions such as the Ingenuity helicopter have shown the advantages of using novel locomotion modes to increase the scientific return of planetary exploration missions. Legged robots can further expand the reach and capability of future planetary missions by traversing more difficult terrain than wheeled rovers, such as jumping over cracks on the ground or traversing rugged terrain with boulders. To develop and test algorithms for using quadruped robots, the AAPLE project was carried out at DFKI. As part of the project, we conducted a series of field experiments on the Volcano on the Aeolian island of Vulcano, an active stratovolcano near Sicily, Italy. The experiments focused on validating newly developed state-of-the-art adaptive optimal control algorithms for quadrupedal locomotion in a high-fidelity analog environment for Lunar and Martian surfaces. This paper presents the technical approach, test plan, software architecture, field deployment strategy, and evaluation results from the Vulcano campaign.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
