Combined shape, appearance and silhouette for simultaneous manipulator and object tracking

Paul Hebert, Nicolas Hudson, Jeremy Ma, Thomas Howard, Thomas Fuchs, Max Bajracharya, Joel Burdick

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

35 Scopus citations

Abstract

This paper develops an estimation framework for sensor-guided manipulation of a rigid object via a robot arm. Using an unscented Kalman Filter (UKF), the method combines dense range information (from stereo cameras and 3D ranging sensors) as well as visual appearance features and silhouettes of the object and manipulator to track both an object-fixed frame location as well as a manipulator tool or palm frame location. If available, tactile data is also incorporated. By using these different imaging sensors and different imaging properties, we can leverage the advantages of each sensor and each feature type to realize more accurate and robust object and reference frame tracking. The method is demonstrated using the DARPA ARM-S system, consisting of a Barrett™WAM manipulator.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2405-2412
Number of pages8
ISBN (Print)9781467314039
DOIs
StatePublished - 1 May 2012
Externally publishedYes
Event 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 - Saint Paul, MN, United States
Duration: 14 May 201218 May 2012

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
Country/TerritoryUnited States
CitySaint Paul, MN
Period14/05/1218/05/12

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