Artistic pen drawing on an arbitrary surface using an impedance-controlled robot

Daeun Song, Taekhee Lee, Young J. Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

34 Scopus citations

Abstract

We present a semi-autonomous robotic pen-drawing system that is capable of creating pen art on an arbitrary surface with varying thickness of pen strokes but without reconstructing the surface explicitly. Our robotic system relies on an industrial, seven-degree-of-freedom (7DoF) manipulator that can be both position- and impedance-controlled. We use a vector-graphics engine to take an artist's pen drawing as input and generate Bézier spline curves with varying offsets. In order to estimate geometric details of the target, unknown surface, during drawing, we rely on incremental and adaptive sampling on the surface using a combination of position and impedance control. Then, our control algorithm physically replicates this drawing on any arbitrary, continuous surface by impedance-controlling the manipulator. We demonstrate that our system can create visually-pleasing and complicated artistic pen drawings on general surfaces without explicit surface-reconstruction nor visual feedback.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Robotics and Automation, ICRA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4085-4090
Number of pages6
ISBN (Electronic)9781538630815
DOIs
StatePublished - 10 Sep 2018
Event2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia
Duration: 21 May 201825 May 2018

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2018 IEEE International Conference on Robotics and Automation, ICRA 2018
Country/TerritoryAustralia
CityBrisbane
Period21/05/1825/05/18

Bibliographical note

Funding Information:
This project was supported by the NRF in Korea (2017R1A2B3012701). T. Lee was supported by the NRF in Korea (2017R1C1B2007306).

Publisher Copyright:
© 2018 IEEE.

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