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The success of a multi-kilometre drive by a solar-powered rover at the lunarsouth pole depends upon careful planning in space and time due to highlydynamic solar illumination conditions. An additional challenge is that therover may be subject to random faults that can temporarily delay long-rangetraverses. The majority of existing global spatiotemporal planners assume adeterministic rover-environment model and do not account for random faults. Inthis paper, we consider a random fault profile with a known, average spatialfault rate. We introduce a methodology to compute recovery policies thatmaximize the probability of survival of a solar-powered rover from differentstart states. A recovery policy defines a set of recourse actions to reach asafe location with sufficient battery energy remaining, given the local solarillumination conditions. We solve a stochastic reach-avoid problem usingdynamic programming to find an optimal recovery policy. Our focus, in part, ison the implications of state space discretization, which is required inpractical implementations. We propose a modified dynamic programming algorithmthat conservatively accounts for approximation errors. To demonstrate thebenefits of our approach, we compare against existing methods in scenarioswhere a solar-powered rover seeks to safely exit from permanently shadowedregions in the Cabeus area at the lunar south pole. We also highlight therelevance of our methodology for mission formulation and trade safety analysisby comparing different rover mobility models in simulated recovery drives fromthe LCROSS impact region.

Recovery Policies for Safe Exploration of Lunar Permanently Shadowed Regions by a Solar-Powered Rover