Abstract:
Three dimensional terrain maps are useful representations
of environments for various robotic applications.
Unfortunately, sensor data (from which such maps are
built) is uncertain and contains errors which are usually
not accounted for in existing terrain building algorithms.
In real-time applications, it is necessary to quantify these
uncertainties to allow map construction decisions to be
made online. This paper addresses this issue by providing
a representation that explicitly accounts for sensing uncertainty.
This is achieved through the use of stochastic
simulation techniques. The result is in an algorithm for
online 3D multi-resolution surface reconstruction of unknown,
and unstructured environments. Results of the
surface reconstruction algorithm in a real environment
are presented.
