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Completed TRL 3 (started at 2, targeting 3)
Within the past two decades, the detection of lava tubes on the Moon and Mars has revealed potential locations that could be susceptible to life beyond Earth. While missions to explore planetary caves through skylights have been proposed, they are prohibitively expensive and require the most advanced mobility systems to traverse perilous terrain; it is recommended to survey a variety of locations to determine the most viable location for future mission success.
Ground Penetrating Radar (GPR) is currently used to locate voids when their vicinity is known. This naturally leads to the question, how can existing subsurface imaging technology be used to better explore unfamiliar spaces rather than passively identifying features when their general location is known in advance? We propose a learning-based approach to identify relevant subsurface features around and above planetary caves to plan optimal trajectories for exploratory ground and aerial vehicles.
GPR can be used to characterize the subsurface as a robot traverses a trajectory to determine how to optimally explore an unknown space. By understanding the recurrence of subsurface features, a robot can optimally re-plan its trajectory to follow a path greater with certainty of reaching a desired goal. In order to better detect features indicative of planetary caves, a multimodal sensing approach will be used to classify detectable surface, subsurface, thermal, and magnetic properties. Heterogeneous multi-agent planning can be used as a force multiplier to more quickly search spaces with systems of varying capability.
This work is applicable to analysis of radar feedback from the Mars Reconnaissance Orbiter and to support efficient subsurface modeling for the Mars 2020 Radar Imager for Mars' Subsurface Experiment (RIMFAX). The methods proposed for sensing and planning will help NASA's missions to characterize the Martian and lunar subsurface and guide future expeditions to explore planetary pits and caves.
The methods proposed for sensing and planning will help NASA's missions to characterize the Martian and lunar subsurface and guide future expeditions to explore planetary pits and caves.
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