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Zero-BEV: Zero-shot Projection of Any First-Person Modality to BEV Maps
Bird's-eye view (BEV) maps are an important geometrically structured representation widely used in robotics, in particular self-driving vehicles and terrestrial robots.
Learning to navigate efficiently and precisely in real environments
In the context of autonomous navigation of terrestrial robots, the creation of realistic models for agent dynamics and sensing is a widespread habit in the robotics literature and in commercial applications, where they are used for model based control and/or for localization and mapping.
Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction
Agents navigating in 3D environments require some form of memory, which should hold a compact and actionable representation of the history of observations useful for decision taking and planning.
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