Policy-contingent abstraction for robust robot control.

J. Pineau, G. Gordon, and S. Thrun.

This paper presents a scalable control algorithm that enables a deployed mobile robot to make high-level control decisions under full consideration of its probabilistic belief. We draw on insights from the rich literature of structured robot controllers and hierarchical MDPs to propose PolCA, a hierarchical probabilistic control algorithm which learns both subtask-specific state abstractions and policies. The resulting controller has been successfully implemented onboard a mobile robotic assistant deployed in a nursing facility. To the best of our knowledge, this work is a unique instance of applying POMDPs to highlevel robotic control problems.

The full paper is available in PDF and gzipped Postscript

@INPROCEEDINGS{Pineau03b,
  AUTHOR	= {Pineau, J. and Gordon, G. and Thrun, S.},
  TITLE		= {Policy-contingent abstraction for robust robot control},
  YEAR		= {2003},
  BOOKTITLE	= {Proceedings of the Conference on Uncertainty in AI (UAI)},
  ADDRESS       = {Acapulco, Mexico}
}