Robohub.org
 

Calligraphy robot uses a Motion Copy System to reproduce detailed brushwork


by
11 October 2012



share this:
12-0181-r

A research group at Keio University, led by Seiichiro Katsura, has developed the Motion Copy System. This system can identify and store detailed brush strokes, based on information about movement in calligraphy. This enables a robot to faithfully reproduce the detailed brush strokes.

This system stores calligraphy movements by using a brush where the handle and tip are separate. The two parts are connected, with the head as the master system and the tip as the slave system. Characters can be written by handling the device in the same way as an ordinary brush.

Unlike conventional motion capture systems, a feature of this one is, it can record and reproduce the force applied to the brush as well as the sensation when you touch something. Until now, passing on traditional skills has depended on intuition and experience. It’s hoped that this new system will enable skills to be learned more efficiently.

“What’s new is, there’s a motor attached to the brush, so while the person’s moving, the motion and force are recorded as digital data using the motor. What’s more, with this technology, the recorded motion and force can be reproduced anytime, anywhere using the motor.”

“We’ve succeeded in using the motor to record the movements of a veteran calligrapher, and to actually reproduce them. So, I think we’ve demonstrated that, to record and reproduce human skills, it’s necessary to record not just motions, but also how strongly those motions are made.”

Looking at the graph of position and brush pressure, the position of the master system and the motion of the slave system are consistent, and also, the pressure shows the opposite waveform. This shows that the law of action and reaction is being artificially implemented between the master and slave systems.

“Currently, multimedia only uses audiovisual information. But we’d like to bring force, action, and motion into IT, by reproducing this kind of physical force via a network, or storing skills on a hard disk for downloading. So, with this new form of IT, you’d be able to access skill content.”




DigInfo TV is a Tokyo-based online video news platform dedicated to producing original coverage of cutting edge technology, research and products from Japan.
DigInfo TV is a Tokyo-based online video news platform dedicated to producing original coverage of cutting edge technology, research and products from Japan.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Robot Talk Episode 168 – Advancing robotics with novel electronics, with Zlatka Stoeva

  30 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Zlatka Stoeva from DZP Technologies about flexible, stretchable and soft printed electronics for dexterous robots.

Competing in RoboCup@Home and winning the 2026 best paper award: an interview with Raphael Memmesheimer

and   28 Oct 2026
Hear more about Raphael's research and his involvement in the RoboCup@Home league.

Robots in Society, Business and Culture: September 2026

We showcase a selection of robotics stories from society, business, research and culture.

Robot Talk Episode 167 – Automating construction, with Jan Petrš

  23 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Jan Petrš from École Polytechnique Fédérale de Lausanne about novel robot designs for construction and architecture.

ACM SIGAI Autonomous Agents Award 2027 open for nominations

  20 Oct 2026
Nominations are solicited for the 2027 ACM SIGAI Autonomous Agents Research Award.

Powered by muscle cells, a paper-thin robot swims through watery maze

  19 Oct 2026
MIT engineers’ new aquabot offers a way to design small, efficient “biohybrid” robots.

Robot Talk Episode 166 – Evolving robot bodies and brains, with Rika Antonova

  16 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Rika Antonova from the University of Cambridge about using artificial intelligence to develop complimentary robot hardware and algorithms.


↑


AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence