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 proceeding › Conference 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 -
