Robot Drawing on a Moving Paperboard

Cheng, C; Li, T; Woolfrey, J; Zhao, L; Huang, S

Robot Drawing on a Moving Paperboard

Cheng, C Li, T Woolfrey, J Zhao, L Huang, S

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Publication Type:: Conference Proceeding
Citation:: Australasian Conference on Robotics and Automation Acra, 2024, 2024-November
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Cheng, C
dc.contributor.author	Li, T
dc.contributor.author	Woolfrey, J
dc.contributor.author	Zhao, L
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178
dc.date.accessioned	2025-06-19T02:34:19Z
dc.date.available	2025-06-19T02:34:19Z
dc.date.issued	2024-01-01
dc.identifier.citation	Australasian Conference on Robotics and Automation Acra, 2024, 2024-November
dc.identifier.issn	1448-2053
dc.identifier.uri	http://hdl.handle.net/10453/187787
dc.description.abstract	Robustness to uncertainties is crucial to collaborative robot control, particularly when performing tasks under unpredictable external influences. One important class of challenging problems is controlling the robot to perform a specific task on a target that undergoes random movements. To address this challenge, we consider the problem of using a robot manipulator to draw a given shape on a paperboard that can have unpredictable small movements. An electromagnetic sensor is used to monitor the pose of the paperboard. We design an MPC (Model Predictive Control) controller and compared it with a few different feedback control strategies for the robot to draw the required shape on the paperboard. Simulations and physical experiments using a Dobot demonstrate that using the electromagnetic sensor information as feedback combined with different control strategies can allow for accurate drawing. A video of our experiments is available at https://youtu.be/Wmj0GU5CYH4?si=cgnN9D3VRr0ZLRlK.
dc.language	en
dc.relation.ispartof	Australasian Conference on Robotics and Automation Acra
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Robot Drawing on a Moving Paperboard
dc.type	Conference Proceeding
utslib.citation.volume	2024-November
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Robotics Institute (RI)
utslib.copyright.status	open_access	*
dc.date.updated	2025-06-19T02:34:16Z
pubs.publication-status	Published
pubs.volume	2024-November

Abstract:

Robustness to uncertainties is crucial to collaborative robot control, particularly when performing tasks under unpredictable external influences. One important class of challenging problems is controlling the robot to perform a specific task on a target that undergoes random movements. To address this challenge, we consider the problem of using a robot manipulator to draw a given shape on a paperboard that can have unpredictable small movements. An electromagnetic sensor is used to monitor the pose of the paperboard. We design an MPC (Model Predictive Control) controller and compared it with a few different feedback control strategies for the robot to draw the required shape on the paperboard. Simulations and physical experiments using a Dobot demonstrate that using the electromagnetic sensor information as feedback combined with different control strategies can allow for accurate drawing. A video of our experiments is available at https://youtu.be/Wmj0GU5CYH4?si=cgnN9D3VRr0ZLRlK.

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http://hdl.handle.net/10453/187787