Spatial Coverage Planning and Optimization for a Planetory Exploration Rover

We are developing onboard planning and execution technology to support the exploration and characterization of geological features by autonomous rovers. In order to generate high quality mission plans, an autonomous rover must reason about the relative importance of the observations it can perform. There are a variety of criteria that may contribute to the importance of an observation such as how well the observation is expected to contribute to different scientific themes (e.g. geology, atmospheric studies) or to engineering tasks. In this paper we look at the scientific criteria of selecting observations that improve the quality of the area covered by samples. Our approach makes use of a priori information, if available, and allows scientists to mark sub-regions of the area with relative priorities for exploration. We use an efficient algorithm for prioritizing observations based on spatial coverage that allows the system to update observation rankings as new information is gained during execution.