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MANIPULATION

Teaching Robots To Draw

Atsunobu Kotani, Stefanie Tellex

Year
2019
Citations
49

Abstract

In this paper, we introduce an approach which enables manipulator robots to write handwritten characters or line drawings. Given an image of just-drawn handwritten characters, the robot infers a plan to replicate the image with a writing utensil, and then reproduces the image. Our approach draws each target stroke in one continuous drawing motion and does not rely on handcrafted rules or on predefined paths of characters. Instead, it learns to write from a dataset of demonstrations. We evaluate our approach in both simulation and on two real robots. Our model can draw handwritten characters in a variety of languages which are disjoint from the training set, such as Greek, Tamil, or Hindi, and also reproduce any stroke-based drawing from an image of the drawing.

Keywords

RobotComputer scienceArtificial intelligenceVariety (cybernetics)Image (mathematics)Set (abstract data type)Disjoint setsPlan (archaeology)TamilHindi

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