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 Brooks, A. |
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Parametric POMDPs: Planning in Continuous spaces for mobile robot navigation
VDM Verlag, Saarbrucken, Deutschland, 2009, ISSN. 978-3-639-15627-0
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Abstract
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 to probability distributions.
Theoretical and practical results are presented which show that, when
compared with similar methods from the literature, this approach is
capable of scaling to larger and more realistic problems.
The algorithms have been implemented and demonstrated during real-time
control of a mobile robot in a challenging navigation task. Results
show that this approach produces significantly more robust behaviour
when compared with heuristic planners which consider only the most
likely states and outcomes.
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