  We consider the navigation of mobile robots in crowded environments, for
which onboard sensing of the crowd is typically limited by occlusions. We
address the problem of inferring the human occupancy in the space around the
robot, in blind spots, beyond the range of its sensing capabilities. This
problem is rather unexplored in spite of the important impact it has on the
robot crowd navigation efficiency and safety, which requires the estimation and
the prediction of the crowd state around it. In this work, we propose the first
solution to sample predictions of possible human presence based on the state of
a fewer set of sensed people around the robot as well as previous observations
of the crowd activity.
