An online algorithm for constrained POMDPs
Name
How-2010-An online algorithm for constrained POMDPs.pdf
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298.38 KB
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Author(s)
Undurti, Aditya
How, Jonathan P.
Date Issued
July 2010
Journal
2010 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers
Citation
Undurti, Aditya, and Jonathan P How. “An Online Algorithm for Constrained POMDPs.” 2010 IEEE International Conference on Robotics and Automation. Anchorage, AK, 2010. 3966-3973. © Copyright 2010 IEEE
Version
Final published version
Abstract
This work seeks to address the problem of planning in the presence of uncertainty and constraints. Such problems arise in many situations, including the basis of this work, which involves planning for a team of first responders (both humans and robots) operating in an urban environment. The problem is framed as a Partially-Observable Markov Decision Process (POMDP) with constraints, and it is shown that even in a relatively simple planning problem, modeling constraints as large penalties does not lead to good solutions. The main contribution of the work is a new online algorithm that explicitly ensures constraint feasibility while remaining computationally tractable. Its performance is demonstrated on an example problem and it is demonstrated that our online algorithm generates policies comparable to an offline constrained POMDP algorithm.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/ROBOT.2010.5509743
