Teleoperation for a Ballcatching Task with Significant Dynamics

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Title: Teleoperation for a Ballcatching Task with Significant Dynamics
Author: Smith, Christian ; Bratt, Mattias ; Christensen, Henrik I.
Abstract: In this paper we present ongoing work on how to incorporate human motion models into the design of a high performance teleoperation platform. A short description of human motion models used for ballcatching is followed by a more detailed study of a teleoperation platform on which to conduct experiments. Also, a pilot study using minimum jerk theory to explain user input behavior in teleoperated catching is presented.
Description: This is the author’s version of a work that was accepted for publication in Neural Networks. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in IEEE Trans on Neural Networks 21, 4 (May 2008), 604-620. doi:10.1016/j.neunet.2008.03.011
Type: Article
ISSN: 0893-6080
Citation: Smith, C., Bratt, M., and Christensen, H. I. Teleoperation for a ballcatching task with significant dynamics. IEEE Trans on Neural Networks 21, 4 (May 2008), 604-620.
Date: 2008-05
Contributor: Georgia Institute of Technology. College of Computing
Georgia Institute of Technology. Center for Robotics and Intelligent Machines
Kungl. Tekniska Högskolan. Centrum för Autonoma System
Publisher: Georgia Institute of Technology
Subject: Teleoperation
High performance manipulation
Human motion

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