Neural Learning and Kalman Filtering Enhanced Teaching by Demonstration for a Baxter Robot

Andy SK Annamalai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

— In this paper, Kalman filter has been successfully
carried out to fuse the data obtained from a Kinect sensor and
a pair of MYO armbands. To do this, the Kinect sensor is used
to capture movements of operators which is programmed by
Microsoft Visual Studio. Operator wears two MYO armbands
with the inertial measurement unit (IMU) embedded to measure
the angular velocity of upper arm motion for the human
operator. Additionally a neural networks (NN) control upgraded
Teaching by Demonstration (TbD) technology has been designed
and it also has been actualized on the Baxter robot. A series of
experiments have been completed to test the performance of the
proposed technique, which has been proved to be an executed
approach for the Baxter robot's TbD has been designed.
Original languageEnglish
Title of host publicationThe 23rd International Conference on Automation and Computing
Place of Publication University of Huddersfield
Pages108-113
Number of pages6
Publication statusPublished - 7 Sep 2017

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  • Cite this

    Annamalai, A. SK. (2017). Neural Learning and Kalman Filtering Enhanced Teaching by Demonstration for a Baxter Robot. In The 23rd International Conference on Automation and Computing (pp. 108-113).