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Adaptive collision-free reaching skill learning from demonstration

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

Standard

Adaptive collision-free reaching skill learning from demonstration. / Ogenyi, Uchenna Emeoha; Zhou, Dalin; Ju, Zhaojie; Liu, Honghai.

ICRRI 2020: Robotics and Rehabilitation Intelligence: First International Conference, ICRRI 2020, Fushun, China, September 9–11, 2020, Proceedings, Part II. ed. / Jianhua Qian; Honghai Liu; Jiangtao Cao; Dalin Zhou. Springer, 2021. p. 105-118 (Communications in Computer and Information Science; Vol. 1336).

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

Harvard

Ogenyi, UE, Zhou, D, Ju, Z & Liu, H 2021, Adaptive collision-free reaching skill learning from demonstration. in J Qian, H Liu, J Cao & D Zhou (eds), ICRRI 2020: Robotics and Rehabilitation Intelligence: First International Conference, ICRRI 2020, Fushun, China, September 9–11, 2020, Proceedings, Part II. Communications in Computer and Information Science, vol. 1336, Springer, pp. 105-118, 1st International Conference on Robotics and Rehabilitation Intelligence, Fushun, China, 9/09/20. https://doi.org/10.1007/978-981-33-4932-2_8

APA

Ogenyi, U. E., Zhou, D., Ju, Z., & Liu, H. (2021). Adaptive collision-free reaching skill learning from demonstration. In J. Qian, H. Liu, J. Cao, & D. Zhou (Eds.), ICRRI 2020: Robotics and Rehabilitation Intelligence: First International Conference, ICRRI 2020, Fushun, China, September 9–11, 2020, Proceedings, Part II (pp. 105-118). (Communications in Computer and Information Science; Vol. 1336). Springer. https://doi.org/10.1007/978-981-33-4932-2_8

Vancouver

Ogenyi UE, Zhou D, Ju Z, Liu H. Adaptive collision-free reaching skill learning from demonstration. In Qian J, Liu H, Cao J, Zhou D, editors, ICRRI 2020: Robotics and Rehabilitation Intelligence: First International Conference, ICRRI 2020, Fushun, China, September 9–11, 2020, Proceedings, Part II. Springer. 2021. p. 105-118. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-33-4932-2_8

Author

Ogenyi, Uchenna Emeoha ; Zhou, Dalin ; Ju, Zhaojie ; Liu, Honghai. / Adaptive collision-free reaching skill learning from demonstration. ICRRI 2020: Robotics and Rehabilitation Intelligence: First International Conference, ICRRI 2020, Fushun, China, September 9–11, 2020, Proceedings, Part II. editor / Jianhua Qian ; Honghai Liu ; Jiangtao Cao ; Dalin Zhou. Springer, 2021. pp. 105-118 (Communications in Computer and Information Science).

Bibtex

@inproceedings{47ceb580b734437b84f7d48513e07ad6,
title = "Adaptive collision-free reaching skill learning from demonstration",
abstract = "In this paper, we considered the task of the robot learning low-level trajectory task in a novel clustered constraint environment. We propose a novel adaptive trajectory algorithm used to generate the necessary trajectory which satisfies the constraint of avoiding collision with an obstacle. Our approach is based on Gaussian mixture model which decomposes the trajectory into several ellipses since the isoline of a single Gaussian model is also an ellipse. Moreover, we employed the principle of the artificial potential field to modify the direction of the motion in the presence of obstacles. Since our approach is based on the underlying reactive skill dynamics, it does not share the same disadvantages as approaches which assume both the model of the task trajectory and the response from the obstacle should be learned from the demonstrations.",
author = "Ogenyi, {Uchenna Emeoha} and Dalin Zhou and Zhaojie Ju and Honghai Liu",
year = "2021",
month = jan,
day = "3",
doi = "10.1007/978-981-33-4932-2_8",
language = "English",
isbn = "978-981-33-4931-5",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "105--118",
editor = "Jianhua Qian and Honghai Liu and Jiangtao Cao and Dalin Zhou",
booktitle = "ICRRI 2020: Robotics and Rehabilitation Intelligence",
note = "1st International Conference on Robotics and Rehabilitation Intelligence, ICRRI 2020 ; Conference date: 09-09-2020 Through 11-09-2020",

}

RIS

TY - GEN

T1 - Adaptive collision-free reaching skill learning from demonstration

AU - Ogenyi, Uchenna Emeoha

AU - Zhou, Dalin

AU - Ju, Zhaojie

AU - Liu, Honghai

PY - 2021/1/3

Y1 - 2021/1/3

N2 - In this paper, we considered the task of the robot learning low-level trajectory task in a novel clustered constraint environment. We propose a novel adaptive trajectory algorithm used to generate the necessary trajectory which satisfies the constraint of avoiding collision with an obstacle. Our approach is based on Gaussian mixture model which decomposes the trajectory into several ellipses since the isoline of a single Gaussian model is also an ellipse. Moreover, we employed the principle of the artificial potential field to modify the direction of the motion in the presence of obstacles. Since our approach is based on the underlying reactive skill dynamics, it does not share the same disadvantages as approaches which assume both the model of the task trajectory and the response from the obstacle should be learned from the demonstrations.

AB - In this paper, we considered the task of the robot learning low-level trajectory task in a novel clustered constraint environment. We propose a novel adaptive trajectory algorithm used to generate the necessary trajectory which satisfies the constraint of avoiding collision with an obstacle. Our approach is based on Gaussian mixture model which decomposes the trajectory into several ellipses since the isoline of a single Gaussian model is also an ellipse. Moreover, we employed the principle of the artificial potential field to modify the direction of the motion in the presence of obstacles. Since our approach is based on the underlying reactive skill dynamics, it does not share the same disadvantages as approaches which assume both the model of the task trajectory and the response from the obstacle should be learned from the demonstrations.

U2 - 10.1007/978-981-33-4932-2_8

DO - 10.1007/978-981-33-4932-2_8

M3 - Conference contribution

SN - 978-981-33-4931-5

T3 - Communications in Computer and Information Science

SP - 105

EP - 118

BT - ICRRI 2020: Robotics and Rehabilitation Intelligence

A2 - Qian, Jianhua

A2 - Liu, Honghai

A2 - Cao, Jiangtao

A2 - Zhou, Dalin

PB - Springer

T2 - 1st International Conference on Robotics and Rehabilitation Intelligence

Y2 - 9 September 2020 through 11 September 2020

ER -

ID: 23171026