  Navigation in dense crowds is a well-known open problem in robotics with many
challenges in mapping, localization, and planning. Traditional solutions
consider dense pedestrians as passive/active moving obstacles that are the
cause of all troubles: they negatively affect the sensing of static scene
landmarks and must be actively avoided for safety. In this paper, we provide a
new perspective: the crowd flow locally observed can be treated as a sensory
measurement about the surrounding scenario, encoding not only the scene's
traversability but also its social navigation preference. We demonstrate that
even using the crowd-flow measurement alone without any sensing about static
obstacles, our method still accomplishes good results for mapping,
localization, and social-aware planning in dense crowds. Videos of the
experiments are available at https://sites.google.com/view/crowdmapping.
