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Automatic learning of pushing strategy for delivery of irregular-shaped objects

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Automatic learning of pushing strategy for delivery of irregular-shaped objects. / Lau, Manfred; Mitani, Jun; Igarashi, Takeo.
Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE Xplore, 2011. p. 3733-3738 .

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Lau, M, Mitani, J & Igarashi, T 2011, Automatic learning of pushing strategy for delivery of irregular-shaped objects. in Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE Xplore, pp. 3733-3738 , IEEE International Conference on Robotics and Automation (ICRA), China, 9/05/11. https://doi.org/10.1109/ICRA.2011.5979740

APA

Lau, M., Mitani, J., & Igarashi, T. (2011). Automatic learning of pushing strategy for delivery of irregular-shaped objects. In Robotics and Automation (ICRA), 2011 IEEE International Conference on (pp. 3733-3738 ). IEEE Xplore. https://doi.org/10.1109/ICRA.2011.5979740

Vancouver

Lau M, Mitani J, Igarashi T. Automatic learning of pushing strategy for delivery of irregular-shaped objects. In Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE Xplore. 2011. p. 3733-3738 doi: 10.1109/ICRA.2011.5979740

Author

Lau, Manfred ; Mitani, Jun ; Igarashi, Takeo. / Automatic learning of pushing strategy for delivery of irregular-shaped objects. Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE Xplore, 2011. pp. 3733-3738

Bibtex

@inproceedings{ea4a7612c5f14ed4b15adb6e6d4c0eb0,
title = "Automatic learning of pushing strategy for delivery of irregular-shaped objects",
abstract = "Object delivery by pushing objects with mobile robots on a flat surface has been successfully demonstrated. However, existing methods can push objects that have a circular or rectangular shape. In this paper, we introduce a learning-based approach for pushing objects of any irregular shape to user-specified goal locations. We first automatically collect a set of data on how an irregular-shaped object moves given the robot's relative position and pushing direction. We collect this data with a randomized approach, and we demonstrate that this approach can successfully collect useful data. Object delivery is achieved by using the collected data with a nonparametric regression method. We demonstrate our approach with a number of irregular-shaped objects.",
keywords = "Collision avoidance , Humans , Mobile robots, Robot kinematics , Shape, Trajectory",
author = "Manfred Lau and Jun Mitani and Takeo Igarashi",
year = "2011",
doi = "10.1109/ICRA.2011.5979740",
language = "English",
isbn = "978-1-61284-386-5",
pages = "3733--3738 ",
booktitle = "Robotics and Automation (ICRA), 2011 IEEE International Conference on",
publisher = "IEEE Xplore",
note = "IEEE International Conference on Robotics and Automation (ICRA) ; Conference date: 09-05-2011",

}

RIS

TY - GEN

T1 - Automatic learning of pushing strategy for delivery of irregular-shaped objects

AU - Lau, Manfred

AU - Mitani, Jun

AU - Igarashi, Takeo

PY - 2011

Y1 - 2011

N2 - Object delivery by pushing objects with mobile robots on a flat surface has been successfully demonstrated. However, existing methods can push objects that have a circular or rectangular shape. In this paper, we introduce a learning-based approach for pushing objects of any irregular shape to user-specified goal locations. We first automatically collect a set of data on how an irregular-shaped object moves given the robot's relative position and pushing direction. We collect this data with a randomized approach, and we demonstrate that this approach can successfully collect useful data. Object delivery is achieved by using the collected data with a nonparametric regression method. We demonstrate our approach with a number of irregular-shaped objects.

AB - Object delivery by pushing objects with mobile robots on a flat surface has been successfully demonstrated. However, existing methods can push objects that have a circular or rectangular shape. In this paper, we introduce a learning-based approach for pushing objects of any irregular shape to user-specified goal locations. We first automatically collect a set of data on how an irregular-shaped object moves given the robot's relative position and pushing direction. We collect this data with a randomized approach, and we demonstrate that this approach can successfully collect useful data. Object delivery is achieved by using the collected data with a nonparametric regression method. We demonstrate our approach with a number of irregular-shaped objects.

KW - Collision avoidance

KW - Humans

KW - Mobile robots

KW - Robot kinematics

KW - Shape

KW - Trajectory

U2 - 10.1109/ICRA.2011.5979740

DO - 10.1109/ICRA.2011.5979740

M3 - Conference contribution/Paper

SN - 978-1-61284-386-5

SP - 3733

EP - 3738

BT - Robotics and Automation (ICRA), 2011 IEEE International Conference on

PB - IEEE Xplore

T2 - IEEE International Conference on Robotics and Automation (ICRA)

Y2 - 9 May 2011

ER -