Traversability mapping for autonomous navigation in unstructured
environments has been widely investigated for decades. However, it
remains challenging due to the uncertainty in geometry perception and
the simplified representation of traversability maps that fail to
capture detailed structures of environments. We propose PTS-Map, a 2.5D
probabilistic terrain state map to address these issues. PTS-Map
sequentially updates the ground surface state and above-ground
elevation state, explicitly distinguishing the geometric features of
ground and obstacles. During state updates, we introduce a novel ground
uncertainty estimation to mitigate the effects of unreliable feature
measurements. By effectively designing the terrain states and
addressing the uncertainty of the ground surface, PTS-Map constructs a
temporally consistent traversability map that provides precise ground
conditions and vertical features relevant to navigation. Experiments
are conducted in various large-scale unstructured environments with
distinct characteristics. PTS-Map outperforms other state-of-the-art
methods in success rate and efficiency by constructing a precise
traversability map of the environments.