Title:
In-Hand Radio Frequency Identification (RFID) for Robotic Manipulation

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dc.contributor.author Deyle, Travis en_US
dc.contributor.author Tralie, Christopher J. en_US
dc.contributor.author Reynolds, Matthew S. en_US
dc.contributor.author Kemp, Charles C. en_US
dc.contributor.corporatename Duke University. Dept. of Electrical and Computer Engineering en_US
dc.contributor.corporatename Georgia Institute of Technology. Healthcare Robotics Lab en_US
dc.contributor.corporatename Georgia Institute of Technology. Institute for Robotics and Intelligent Machines en_US
dc.date.accessioned 2013-12-19T15:22:27Z
dc.date.available 2013-12-19T15:22:27Z
dc.date.issued 2013-05
dc.description ©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. en_US
dc.description Presented at the 2013 IEEE International Conference on Robotics and Automation (ICRA) Karlsruhe, Germany, May 6-10, 2013. en_US
dc.description DOI: 10.1109/ICRA.2013.6630729 en_US
dc.description.abstract We present a unique multi-antenna RFID reader (a sensor) embedded in a robot's manipulator that is designed to operate with ordinary UHF RFID tags in a short-range, near-field electromagnetic regime. Using specially designed near-field antennas enables our sensor to obtain spatial information from tags at ranges of less than 1 meter. In this work, we characterize the near-field sensor's ability to detect tagged objects in the robots manipulator, present robot behaviors to determine the identity of a grasped object, and investigate how additional RF signal properties can be used for “pre-touch” capabilities such as servoing to grasp an object. The future combination of long-range (far-field) and short-range (near-field) UHF RFID sensing has the potential to enable roboticists to jump-start applications by obviating or supplementing false-positive-prone visual object recognition. These techniques may be especially useful in the healthcare and service sectors, where mis-identification of an object (for example, a medication bottle) could have catastrophic consequences. en_US
dc.identifier.citation In-Hand Radio Frequency Identification (RFID) for Robotic Manipulation, Travis Deyle, Christopher Tralie, Matthew Reynolds, and Charles C. Kemp, IEEE International Conference on Robotics and Automation (ICRA), 2013, 1234-1241. en_US
dc.identifier.doi 10.1109/ICRA.2013.6630729
dc.identifier.isbn 978-1-4673-5641-1
dc.identifier.issn 1050-4729
dc.identifier.uri http://hdl.handle.net/1853/49851
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers en_US
dc.subject In-hand radio frequency identification en_US
dc.subject RFID en_US
dc.subject Robotic manipulation en_US
dc.subject Visual object recognition en_US
dc.subject Healthcare robotics en_US
dc.title In-Hand Radio Frequency Identification (RFID) for Robotic Manipulation en_US
dc.type Text
dc.type.genre Proceedings
dc.type.genre Post-print
dspace.entity.type Publication
local.contributor.author Kemp, Charles C.
local.contributor.corporatename Healthcare Robotics Lab
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
relation.isAuthorOfPublication e4f743b9-0557-4889-a16e-00afe0715f4c
relation.isOrgUnitOfPublication c6394b0e-6e8b-42dc-aeed-0e22560bd6f1
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
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