An intuitive robot learning from human demonstration

Uchenna Emeoha Ogenyi; Gongyue Zhang; Chenguang Yang; Zhaojie Ju; Honghai Liu

doi:10.1007/978-3-319-97586-3_16

An intuitive robot learning from human demonstration

Uchenna Emeoha Ogenyi, Gongyue Zhang, Chenguang Yang, Zhaojie Ju, Honghai Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

This paper presents a new way to teach a robot certain motions remotely from human demonstrator. The human and robot interface is built using a Kinect sensor which is connected directly to a remote computer that runs on processing software. The Cartesian coordinates are extracted, converted into joint angles and sent to the workstation for the control of the Sawyer robot. Kinesthetic teaching was used to correct the reproduced demonstrations while only valid resolved joint angles are recorded to ensure consistence in the sent data. The recorded dataset is encoded using GMM while GMR was employed to extract and reproduce generalised trajectory with respect to the associated time-step. To evaluate the proposed approach, an experiment for a robot to follow a human arm motion was performed. This proposed approach could help non-expert users to teach a robot how to perform assembling task in more human like ways.

Original language	English
Title of host publication	Intelligent Robotics and Applications
Subtitle of host publication	11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9–11, 2018, Proceedings, Part I
Editors	Zhiyong Chen, Alexandre Mendes, Yamin Yan, Shifeng Chen
Publisher	Springer
Pages	176-185
ISBN (Electronic)	978-3-319-97586-3
ISBN (Print)	978-3-319-97585-6
DOIs	https://doi.org/10.1007/978-3-319-97586-3_16
Publication status	Published - Sept 2018
Event	11th International Conference on Intelligent Robotics and Applications - Australia, Newcastle, Australia Duration: 9 Aug 2018 → 11 Aug 2018 http://www.icira2018.org

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	10984
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Intelligent Robotics and Applications
Abbreviated title	ICIRA 2018
Country/Territory	Australia
City	Newcastle
Period	9/08/18 → 11/08/18
Internet address	http://www.icira2018.org

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10.1007/978-3-319-97586-3_16

An Intuitive Robot Learning from Human Demonstration
The final authenticated version is available online at: http://dx.doi.org/10.1007%2F978-3-319-97586-3_16.
Accepted author manuscript (Post-print), 1.06 MB

Cite this

Ogenyi, U. E., Zhang, G., Yang, C., Ju, Z., & Liu, H. (2018). An intuitive robot learning from human demonstration. In Z. Chen, A. Mendes, Y. Yan, & S. Chen (Eds.), Intelligent Robotics and Applications: 11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9–11, 2018, Proceedings, Part I (pp. 176-185). (Lecture Notes in Computer Science; Vol. 10984). Springer. https://doi.org/10.1007/978-3-319-97586-3_16

Ogenyi, Uchenna Emeoha ; Zhang, Gongyue ; Yang, Chenguang et al. / An intuitive robot learning from human demonstration. Intelligent Robotics and Applications: 11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9–11, 2018, Proceedings, Part I. editor / Zhiyong Chen ; Alexandre Mendes ; Yamin Yan ; Shifeng Chen. Springer, 2018. pp. 176-185 (Lecture Notes in Computer Science).

@inproceedings{fdec9e860b5b4e7eb3f7b3568657016b,

title = "An intuitive robot learning from human demonstration",

abstract = "This paper presents a new way to teach a robot certain motions remotely from human demonstrator. The human and robot interface is built using a Kinect sensor which is connected directly to a remote computer that runs on processing software. The Cartesian coordinates are extracted, converted into joint angles and sent to the workstation for the control of the Sawyer robot. Kinesthetic teaching was used to correct the reproduced demonstrations while only valid resolved joint angles are recorded to ensure consistence in the sent data. The recorded dataset is encoded using GMM while GMR was employed to extract and reproduce generalised trajectory with respect to the associated time-step. To evaluate the proposed approach, an experiment for a robot to follow a human arm motion was performed. This proposed approach could help non-expert users to teach a robot how to perform assembling task in more human like ways.",

author = "Ogenyi, {Uchenna Emeoha} and Gongyue Zhang and Chenguang Yang and Zhaojie Ju and Honghai Liu",

year = "2018",

month = sep,

doi = "10.1007/978-3-319-97586-3_16",

language = "English",

isbn = "978-3-319-97585-6",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "176--185",

editor = "Zhiyong Chen and Alexandre Mendes and Yamin Yan and Shifeng Chen",

booktitle = "Intelligent Robotics and Applications",

note = "11th International Conference on Intelligent Robotics and Applications, ICIRA 2018 ; Conference date: 09-08-2018 Through 11-08-2018",

url = "http://www.icira2018.org",

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Ogenyi, UE, Zhang, G, Yang, C, Ju, Z & Liu, H 2018, An intuitive robot learning from human demonstration. in Z Chen, A Mendes, Y Yan & S Chen (eds), Intelligent Robotics and Applications: 11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9–11, 2018, Proceedings, Part I. Lecture Notes in Computer Science, vol. 10984, Springer, pp. 176-185, 11th International Conference on Intelligent Robotics and Applications, Newcastle, New South Wales, Australia, 9/08/18. https://doi.org/10.1007/978-3-319-97586-3_16

An intuitive robot learning from human demonstration. / Ogenyi, Uchenna Emeoha; Zhang, Gongyue; Yang, Chenguang et al.
Intelligent Robotics and Applications: 11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9–11, 2018, Proceedings, Part I. ed. / Zhiyong Chen; Alexandre Mendes; Yamin Yan; Shifeng Chen. Springer, 2018. p. 176-185 (Lecture Notes in Computer Science; Vol. 10984).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - An intuitive robot learning from human demonstration

AU - Ogenyi, Uchenna Emeoha

AU - Zhang, Gongyue

AU - Yang, Chenguang

AU - Ju, Zhaojie

AU - Liu, Honghai

PY - 2018/9

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N2 - This paper presents a new way to teach a robot certain motions remotely from human demonstrator. The human and robot interface is built using a Kinect sensor which is connected directly to a remote computer that runs on processing software. The Cartesian coordinates are extracted, converted into joint angles and sent to the workstation for the control of the Sawyer robot. Kinesthetic teaching was used to correct the reproduced demonstrations while only valid resolved joint angles are recorded to ensure consistence in the sent data. The recorded dataset is encoded using GMM while GMR was employed to extract and reproduce generalised trajectory with respect to the associated time-step. To evaluate the proposed approach, an experiment for a robot to follow a human arm motion was performed. This proposed approach could help non-expert users to teach a robot how to perform assembling task in more human like ways.

AB - This paper presents a new way to teach a robot certain motions remotely from human demonstrator. The human and robot interface is built using a Kinect sensor which is connected directly to a remote computer that runs on processing software. The Cartesian coordinates are extracted, converted into joint angles and sent to the workstation for the control of the Sawyer robot. Kinesthetic teaching was used to correct the reproduced demonstrations while only valid resolved joint angles are recorded to ensure consistence in the sent data. The recorded dataset is encoded using GMM while GMR was employed to extract and reproduce generalised trajectory with respect to the associated time-step. To evaluate the proposed approach, an experiment for a robot to follow a human arm motion was performed. This proposed approach could help non-expert users to teach a robot how to perform assembling task in more human like ways.

U2 - 10.1007/978-3-319-97586-3_16

DO - 10.1007/978-3-319-97586-3_16

M3 - Conference contribution

SN - 978-3-319-97585-6

T3 - Lecture Notes in Computer Science

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EP - 185

BT - Intelligent Robotics and Applications

A2 - Chen, Zhiyong

A2 - Mendes, Alexandre

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PB - Springer

T2 - 11th International Conference on Intelligent Robotics and Applications

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Ogenyi UE, Zhang G, Yang C, Ju Z , Liu H. An intuitive robot learning from human demonstration. In Chen Z, Mendes A, Yan Y, Chen S, editors, Intelligent Robotics and Applications: 11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9–11, 2018, Proceedings, Part I. Springer. 2018. p. 176-185. (Lecture Notes in Computer Science). Epub 2018 Aug 3. doi: 10.1007/978-3-319-97586-3_16

An intuitive robot learning from human demonstration

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