MIT Libraries logoDSpace@MIT

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

Robotic grasping using POMDPs and machine learning

Author(s)
Perez Bedoya, Ignacio.
Thumbnail
Download1192966361-MIT.pdf (8.675Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Tomas Lozano-Perez.
Terms of use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Robotic grasping is a fundamental problem in robotics. Currently, there is no single approach for finding good policies that are robust enough to deal with real-world uncertainty, a variety of different objects, and real-time execution. In this thesis, I designed and implemented a grasping algorithm that aims to address these shortcomings. The algorithm is based on two key ideas. First, it uses a POMDP to represent the grasping problem, a physics simulator to approximate the real world, and an offline POMDP solver to generate grasping policies. Then, it uses an RNN to learn from the generated policies given a variety of objects to create a real-time robust policy for grasping. Code can be found at git@github.mit.edu:ignapb/grasping.git
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
 
Cataloged from the official PDF of thesis.
 
Includes bibliographical references (pages 59-60).
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/127442
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.