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RI | Publications | Policy-contingent abstraction for robust robot control
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Policy-contingent abstraction for robust robot control
J. Pineau, G. Gordon, and S. Thrun
Conference on Uncertainty in Articifical Intelligence (UAI), August, 2003, pp. 477 - 484.
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| Abstract |
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 high-level robotic control problems.
| Notes |
Associated center: MRTC
Associated lab/group: Robot Learning Lab
Associated project: Personal Robotic Assistants For The Elderly
Number of pages: 8
| Text Reference |
J. Pineau, G. Gordon, and S. Thrun, "Policy-contingent abstraction for robust robot control," Conference on Uncertainty in Articifical Intelligence (UAI), August, 2003, pp. 477 - 484.
| BibTeX Reference |
@inproceedings{Pineau_2003_4827,
author = "Joelle Pineau and Geoffrey Gordon and Sebastian Thrun",
title = "Policy-contingent abstraction for robust robot control",
booktitle = "Conference on Uncertainty in Articifical Intelligence (UAI)",
month = "August",
year = "2003",
pages = "477 - 484"
}