"handwriting robot" seems to be an old concept. This kind of thing is not only sold on the Internet, but has even become a lazy artifact for students to deal with handwritten homework.

(when you search for "handwriting robot", the results look like this)

but what I want to talk about today is not this kind of writing machine that is output completely according to the established program, although they write neatly and beautifully, but they don't have a soul. What I want to show you today is a robot that can "think" about how to write.

(picture source: ATSUNOBU KOTANI)

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when we learn to write symbols in a new language, we always have to learn the stroke order of writing. If we want the robot to hold a pen to write, we usually have to enter instructions on how to handle the pen. But the robot's progress is that even if it sees text symbols that it has never touched before, it can "guess" how to write strokes by giving it a demonstration of writing.

students and researchers from Brown University have developed a deep learning algorithm for the robot. and first of all, it was "trained in writing" with a library of Japanese katakana and Chinese characters (Japanese should be chosen for training because it was mainly developed by a Japanese student). Next, the robot challenged "Hello" to copy 10 characters, including many writing systems that programs had never touched before, such as Korean, Tamil and so on. In addition to copying the text seen for the first time, it can also analyze the stroke composition of the graffiti and draw one of its own following the example.

(demonstration video of copying and drawing in 10 kinds of text. Source: Atsunobu Kotani)

of course, just like when humans think about the order of the pen, the machine will write something different from the general habit, such as the e of hello, which first writes a stroke similar to the inverse s shape, and then fills in the opening in the upper left corner, and there is also an obvious inverted pen when writing "Hello" in Chinese.

related research papers can be found here: https://h2r.cs.brown.edu/wp-content/uploads/kotani19.pdf

report Source: https://www.brown.edu/news/2019-05-15/robowrite