TY - JOUR
T1 - Autonomous visual rendering using physical motion
AU - Prabhakar, Ahalya
AU - Mavrommati, Anastasia
AU - Schultz, Jarvis
AU - Murphey, Todd D.
N1 - Publisher Copyright:
Copyright © 2017, The Authors. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2017/9/8
Y1 - 2017/9/8
N2 - This paper addresses the problem of enabling a robot to repre-sent and recreate visual information through physical motion, focusing on drawing using pens, brushes, or other tools. This work uses ergodicity as a control objective that translates planar visual input to physical motion without preprocessing (e.g., image processing, motion primitives). We achieve comparable results to existing drawing methods, while reducing the algorithmic complexity of the software. We demonstrate that optimal ergodic control algorithms with different time-horizon characteristics (in-finitesimal, finite, and receding horizon) can generate qualitatively and stylistically different motions that render a wide range of visual infor-mation (e.g., letters, portraits, landscapes). In addition, we show that ergodic control enables the same software design to apply to multiple robotic systems by incorporating their particular dynamics, thereby re-ducing the dependence on task-specific robots. Finally, we demonstrate physical drawings with the Baxter robot.
AB - This paper addresses the problem of enabling a robot to repre-sent and recreate visual information through physical motion, focusing on drawing using pens, brushes, or other tools. This work uses ergodicity as a control objective that translates planar visual input to physical motion without preprocessing (e.g., image processing, motion primitives). We achieve comparable results to existing drawing methods, while reducing the algorithmic complexity of the software. We demonstrate that optimal ergodic control algorithms with different time-horizon characteristics (in-finitesimal, finite, and receding horizon) can generate qualitatively and stylistically different motions that render a wide range of visual infor-mation (e.g., letters, portraits, landscapes). In addition, we show that ergodic control enables the same software design to apply to multiple robotic systems by incorporating their particular dynamics, thereby re-ducing the dependence on task-specific robots. Finally, we demonstrate physical drawings with the Baxter robot.
KW - Automation
KW - Motion control
KW - Robot art
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M3 - Article
AN - SCOPUS:85092980438
JO - Free Radical Biology and Medicine
JF - Free Radical Biology and Medicine
SN - 0891-5849
ER -