The success of a multi-kilometre drive by a solar-powered rover at the lunar south pole depends upon careful planning in space and time due to highly dynamic solar illumination conditions. An additional challenge is that real-world robots may be subject to random faults that can temporarily delay long-range traverses. The majority of existing global spatiotemporal planners assume a deterministic rover-environment model and do not account for random faults. In this paper, we consider a random fault profile with a known, average spatial fault rate. We introduce a methodology to compute recovery policies that maximize the probability of survival of a solar-powered rover from different start states. A recovery policy defines a set of recourse actions to reach a location with sufficient battery energy remaining, given the local solar illumination conditions. We solve a stochastic reach-avoid problem using dynamic programming to find such optimal recovery policies. Our focus, in part, is on the implications of state space discretization, which is often required in practical implementations. We propose a modified dynamic programming algorithm that conservatively accounts for approximation errors. To demonstrate the benefits of our approach, we compare against existing methods in scenarios where a solar-powered rover seeks to safely exit from permanently shadowed regions in the Cabeus area at the lunar south pole. We also highlight the relevance of our methodology for mission formulation and trade safety analysis by empirically comparing different rover mobility models in simulated recovery drives from the LCROSS crash region.

翻译：摘要：太阳动力月球车在月球南极完成数公里级行驶的成功，取决于对高度动态太阳光照条件的时空精细规划。实际机器人可能遭受随机故障，导致长距离穿越任务临时延迟，这构成了额外挑战。现有大多数全局时空规划器假定确定性的月球车-环境模型，未考虑随机故障。本文考虑具有已知平均空间故障率的随机故障模型，提出了一种计算方法来生成恢复策略，以最大化太阳动力月球车从不同初始状态下的生存概率。恢复策略定义了基于局部太阳光照条件、使月球车到达剩余电池能量充足位置的补救行动集合。我们利用动态规划求解随机可达-避障问题，从而获得最优恢复策略。部分研究重点在于状态空间离散化（实际实施中的常见需求）所产生的影响。我们提出了一种改进的动态规划算法，能够保守地处理近似误差。为证明本方法的优势，我们在太阳动力月球车需安全撤离月球南极卡比乌斯区域永久阴影区的场景中，与现有方法进行了对比。此外，我们通过从LCROSS撞击坑区域模拟恢复行驶时对不同月球车移动模型进行的经验性比较，突显了本方法在任务规划与权衡安全分析中的相关性。