We present a robust real-time method which
performs dense reconstruction of high quality height maps
from monocular video. By representing the height map as a
triangular mesh, and using efficient differentiable rendering
approach, our method enables rigorous incremental probabilistic
fusion of standard locally estimated depth and colour into
an immediately usable dense model. We present results for
the application of free space and obstacle mapping by a lowcost
robot, showing that detailed maps suitable for autonomous
navigation can be obtained using only a single forward-looking
camera.