为月球着陆任务设计实时重规划算法，确保着陆安全与燃料效率。
Real-Time Retargeting Using Controllability Boundary for Chandrayaan-3 Lunar Landing
- 利用可控制边界凸表示快速判断新着陆点可行性。
- 在真实任务中实现毫秒级目标更新，保障着陆安全。
- 首次在月球任务中应用数据驱动的实时重规划框架。
本文提出了为月球探测器Chandrayaan-3着陆任务设计的实时重规划制导策略。基准制导生成近似燃料最优的下降轨迹，而高层策略可在原定着陆点不可行时，安全重规划至备选着陆点。该策略基于可控制边界的一种凸表示，实现快速可行性验证和实时目标更新。据作者所知，这是首个在实际月球着陆任务中应用的数据驱动重规划框架。飞行前仿真及任务实际结果验证了该方法的有效性。
原文摘要 · Abstract (English)
This paper presents the real-time retargeting guidance policy developed for the Chandrayaan-3 lunar landing mission. The baseline guidance generates approximate fuel-optimal descent trajectories, while a high-level policy enables safe retargeting to alternate sites when the nominal site becomes infeasible. The retargeting strategy leverages a convex representation of the controllability boundary, allowing rapid feasibility checks and real-time target updates. To the best of the authors knowledge, this represents the first application of a data-driven retargeting framework in an operational lunar landing mission. Pre-flight simulations and Chandrayaan-3 flight results validate the effectiveness of the proposed approach.
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