谁在何时于月球表面去了哪里：识别拜占庭漫游车的取证轨迹分析
Who Went Where When on the Lunar Surface: Forensic Trajectory Analysis to Identify Byzantine Rovers
- Adelaide University（阿德莱德大学）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
针对未来月球多漫游车任务中拜占庭漫游车伪造测量数据的问题，提出一种基于可信度归因的轨迹估计方法，通过评估候选子集统计一致性识别恶意漫游车，显著提升轨迹重建精度。
中文摘要 AI 辅助
未来的行星表面任务可能涉及多台独立操作的漫游车共享同一部署区域，这引发了对遵守诸如月球安全区等运行约束进行验证的需求。由于连续的现场可观测性很少可用，这种验证需要从稀疏遥测数据（包括里程计、位姿先验和漫游车间相对检测）中事后重建漫游车轨迹。我们引入了在存在拜占庭智能体（即提供未校准或故意伪造测量数据以支持不正确轨迹的漫游车）情况下，对非合作行星漫游车进行取证轨迹分析的问题。我们表明，标准的鲁棒异常值位姿图优化方法在此场景下是脆弱的，因为拜占庭漫游车可以生成内部一致且数量充足的测量数据，使得真实的、有罪证作用的测量数据看起来像异常值。为解决此问题，我们提出了一种归因感知的轨迹估计方法，该方法推理漫游车的可信度而非单个测量的有效性。该方法通过比较候选可信漫游车子集的内部和边界相对检测与提供的先验的统计一致性来评估这些子集，然后仅使用归因于可信智能体的测量数据来估计轨迹。在合成模拟和真实行星模拟轨迹数据上，所提出的方法能够识别拜占庭漫游车，并产生比现有鲁棒位姿图优化基线显著更准确的轨迹估计。
英文摘要
Future planetary surface missions are likely to involve multiple independently operated rovers sharing the same deployment region, raising the need to verify compliance with operational constraints such as Lunar Safety Zones. Because continuous in-situ observability is rarely available, such verification requires post-hoc reconstruction of rover trajectories from sparse telemetry, including odometry, pose priors, and relative inter-rover detections. We introduce the problem of forensic trajectory analysis for non-cooperative planetary rovers in the presence of Byzantine agents: rovers that provide miscalibrated or deliberately falsified measurements to support an incorrect trajectory. We show that standard outlier-robust pose graph optimisation methods are vulnerable in this setting, because Byzantine rovers can generate measurements that are internally consistent and numerous enough to make truthful incriminating measurements appear as outliers. To address this, we propose an attribution-aware trajectory estimation method that reasons over rover credibility rather than individual measurement validity. The method evaluates candidate credible rover subsets by comparing the statistical consistency of their internal and boundary relative detections against provided priors, and then estimates trajectories using only measurements attributed to credible agents. Across synthetic simulations and real planetary-analogue trajectory data, the proposed method identifies Byzantine rovers and produces significantly more accurate trajectory estimates than existing robust pose graph optimisation baselines.
