MIT Libraries homeMIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

IcLQG: Combining local and global optimization for control in information space

Author(s)
Roy, Nicholas; Huynh, Vu Anh
Thumbnail
DownloadHuynh-2009-IcLQG Combining local and global optimization for control in information space.pdf (340.1Kb)
PUBLISHER_POLICY

Publisher Policy

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.

Terms of use
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.
Metadata
Show full item record
Abstract
When a mobile robot does not have perfect knowledge of its position, conventional controllers can experience failures such as collisions because the uncertainty of the position is not considered in choosing control actions. In this paper, we show how global planning and local feedback control can be combined to generate control laws in the space of distributions over position, that is, in information space. We give a novel algorithm for computing ldquoinformation-constrainedrdquo linear quadratic Gaussian (icLQG) policies for controlling a robot with imperfect state information. The icLQG algorithm uses the belief roadmap algorithm to efficiently search for a trajectory that approximates the globally-optimal motion plan in information space, and then iteratively computes a feedback control law to locally optimize the global approximation. The icLQG algorithm is not only robust to imperfect state information but also scalable to high-dimensional systems and environments. In addition, icLQG is capable of answering multiple queries efficiently. We demonstrate performance results for controlling a vehicle on the plane and a helicopter in three dimensions.
Date issued
2009-07
URI
http://hdl.handle.net/1721.1/59401
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Journal
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009.
Publisher
Institute of Electrical and Electronics Engineers
Citation
Vu Anh Huynh, and N. Roy. “icLQG: Combining local and global optimization for control in information space.” Robotics and Automation, 2009. ICRA '09. IEEE International Conference on. 2009. 2851-2858. © 2009 IEEE
Version: Final published version
Other identifiers
INSPEC Accession Number: 11010176
ISBN
978-1-4244-3803-7

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries homeMIT Libraries logo

Find us on

Twitter Facebook Instagram YouTube RSS

MIT Libraries navigation

SearchHours & locationsBorrow & requestResearch supportAbout us
PrivacyPermissionsAccessibility
MIT
Massachusetts Institute of Technology
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.