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.

Reliably Arranging Objects in Uncertain Domains

Author(s)
Anders, Ariel S; Kaelbling, Leslie P; Lozano-Perez, Tomas
Thumbnail
DownloadAccepted version (3.425Mb)
Terms of use
Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
Metadata
Show full item record
Abstract
A crucial challenge in robotics is achieving reliable results in spite of sensing and control uncertainty. In this work, we explore the conformant planning approach to robot manipulation. In particular, we tackle the problem of pushing multiple planar objects simultaneously to achieve a specified arrangement without external sensing. Conformant planning is a belief-state planning problem. A belief state is the set of all possible states of the world, and the goal is to find a sequence of actions that will bring an initial belief state to a goal belief state. To do forward belief-state planning, we created a deterministic belief-state transition model from supervised learning based on off-line physics simulations. We compare our method with an on-line physics-based manipulation approach and show significantly reduced planning times and increased robustness in simulated experiments. Finally, we demonstrate the success of this approach in simulations and physical robot experiments.
Date issued
2018-09-28
URI
https://hdl.handle.net/1721.1/121463
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
2018 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Anders, Ariel S., et al. “Reliably Arranging Objects in Uncertain Domains.” 2018 IEEE International Conference on Robotics and Automation (ICRA), 21-25 May, 2018, Brisbane, Queensland, Australia, IEEE, 2018, pp. 1603–10.
Version: Author's final manuscript
ISSN
2577-087X

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.