3 accepted papers
While modern deep neural networks are performant perception modules, performance (accuracy) alone is insufficient, particularly for safety-critical robotic applications such as self-driving vehicles. Robot autonomy stacks also require these otherwise blackbox models to produce reliable and calibrate…
In this work, we present MapLite: a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are used to segment the road region and register the topo
Active localization consists of generating robot actions that allow it to maximally disambiguate its pose within a reference map. Traditional approaches use an information-theoretic criterion for action selection and hand-crafted perceptual models. In this work we propose an end-to-end differentiabl