  In a wide range of robotic applications, being able to create a 3D model of
the surrounding environment is a key feature for autonomous tasks. In this
research report, we present a statistical model to perform 3D reconstructions
of the environment from range sensors using an occupancy grid. To do so, we
take into account all the available information obtained from the sensor,
considering the distances traversed by the rays in each cell and seeking to
reduce reconstruction errors caused by discretization. The approach has been
validated qualitatively using the KITTI dataset.
