This book is concerned with planning and acting under
uncertainty in
partially-observable continuous domains. It focusses
on the problem
of mobile robot navigation given a known map. The
dominant paradigm
for robot localisation is to use Bayesian estimation
to maintain a
probability distribution over possible robot poses.
In contrast,
control algorithms often base their decisions on the
assumption that
the most likely state is correct, rather than
considering the entire
distribution.

This book formulates an approach to planning in the
space of
continuous parameterised approximations...