Reducing Uncertainty in Navigation and Exploration
  A significant problem in designing mobile robot control systems involves
coping with the uncertainty that arises in moving about in an unknown or
partially unknown environment and relying on noisy or ambiguous sensor data to
acquire knowledge about that environment. We describe a control system that
chooses what activity to engage in next on the basis of expectations about how
the information re- turned as a result of a given activity will improve 2 its
knowledge about the spatial layout of its environment. Certain of the
higher-level components of the control system are specified in terms of
probabilistic decision models whose output is used to mediate the behavior of
lower-level control components responsible for movement and sensing.
