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Active TRL 2 (started at 2, targeting 3)
The proposed work leverages techniques from computer vision to provide an end-to-end mapping pipeline suitable for NASA's mapping interests of surfaces (e.g. planetary, asteroid). The long-term vision of the proposed end-to-end navigation pipeline is to facilitate longer durations of autonomy for robots, motivated by the fact that communication bandwidths shrink the farther they are from Earth. The objective of this work is (1) to allow a robot to generate a spatially continuous and photo-realistic representation of the environment in real-time through camera images, (2) to perform online, safe navigation through this representation to a desired destination, and (3) to augment navigation with informative planning to increase the fidelity of the map quality. Specifically, the work leverages Neural Radiance Fields (NeRFs) as the desired map representation, on top of which our safe, informative planning pipeline builds upon. The generated photo-realistic map is crucial for applications relating to scientific inquiry, such as surveying areas suitable for lunar or Martian bases, scanning for minerals or features in the landscape, and mapping the geometry of lava tubes.
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