Neural learning and Kalman filtering enhanced teaching by demonstration for a Baxter robot

C. Li; C. Yang; J. Wan; A. Annamalai; A. Cangelosi

doi:10.23919/IConAC.2017.8081985

Neural learning and Kalman filtering enhanced teaching by demonstration for a Baxter robot

C. Li, C. Yang, J. Wan, A. Annamalai, A. Cangelosi

Machine Learning and Robotics

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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 language	English
Title of host publication	IEEE Xplore
Publisher	IEEE
Pages	1-6
Number of pages	6
DOIs	https://doi.org/10.23919/IConAC.2017.8081985
Publication status	Published - 23 Oct 2017
Event	23rd International Conference on Automation and Computing - Huddersfield, United Kingdom Duration: 7 Sept 2017 → 8 Sept 2017

Conference

Conference	23rd International Conference on Automation and Computing
Abbreviated title	ICAC
Country/Territory	United Kingdom
City	Huddersfield
Period	7/09/17 → 8/09/17

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title = "Neural learning and Kalman filtering enhanced teaching by demonstration for a Baxter robot",

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.",

author = "C. Li and C. Yang and J. Wan and A. Annamalai and A. Cangelosi",

year = "2017",

month = oct,

day = "23",

doi = "10.23919/IConAC.2017.8081985",

language = "English",

pages = "1--6",

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publisher = "IEEE",

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note = "23rd International Conference on Automation and Computing, ICAC ; Conference date: 07-09-2017 Through 08-09-2017",

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T1 - Neural learning and Kalman filtering enhanced teaching by demonstration for a Baxter robot

AU - Li, C.

AU - Yang, C.

AU - Wan, J.

AU - Annamalai, A.

AU - Cangelosi, A.

PY - 2017/10/23

Y1 - 2017/10/23

N2 - 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.

AB - 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.

U2 - 10.23919/IConAC.2017.8081985

DO - 10.23919/IConAC.2017.8081985

M3 - Conference contribution

SP - 1

EP - 6

BT - IEEE Xplore

PB - IEEE

T2 - 23rd International Conference on Automation and Computing

Y2 - 7 September 2017 through 8 September 2017

ER -

Neural learning and Kalman filtering enhanced teaching by demonstration for a Baxter robot

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