Learning deposition policies for fused multi-material 3D printing
Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. 2023. Learning deposition policies for fused multi-material 3D printing. 2023 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation.
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Author
Liao, Kang;
Tricard, Thibault;
Piovarci, MichalISTA;
Seidel, Hans-Peter;
Babaei, Vahid
Department
Abstract
3D printing based on continuous deposition of materials, such as filament-based 3D printing, has seen widespread
adoption thanks to its versatility in working with a wide range of materials. An important shortcoming of this type of technology is its limited multi-material capabilities. While there are simple hardware designs that enable multi-material printing in principle, the required software is heavily underdeveloped. A typical hardware design fuses together individual materials fed into a single chamber from multiple inlets before they are deposited. This design, however, introduces a time delay between the intended material mixture and its actual deposition. In this work, inspired by diverse path planning research in robotics, we show that this mechanical challenge can be addressed via improved printer control. We propose to formulate the search for optimal multi-material printing policies in a reinforcement
learning setup. We put forward a simple numerical deposition model that takes into account the non-linear material mixing and delayed material deposition. To validate our system we focus on color fabrication, a problem known for its strict requirements for varying material mixtures at a high spatial frequency. We demonstrate that our learned control policy outperforms state-of-the-art hand-crafted algorithms.
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Publishing Year
Date Published
2023-05-20
Proceedings Title
2023 IEEE International Conference on Robotics and Automation
Acknowledgement
This work is graciously supported by FWF Lise Meitner (Grant M 3319). Kang Liao sincerely thank Emiliano Luci, Chunyu Lin, and Yao Zhao for their huge support.
Conference
ICRA: International Conference on Robotics and Automation
Conference Location
London, United Kingdom
Conference Date
2023-05-29 – 2023-06-02
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Cite this
Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. Learning deposition policies for fused multi-material 3D printing. In: 2023 IEEE International Conference on Robotics and Automation. IEEE; 2023.
Liao, K., Tricard, T., Piovarci, M., Seidel, H.-P., & Babaei, V. (2023). Learning deposition policies for fused multi-material 3D printing. In 2023 IEEE International Conference on Robotics and Automation. London, United Kingdom: IEEE.
Liao, Kang, Thibault Tricard, Michael Piovarci, Hans-Peter Seidel, and Vahid Babaei. “Learning Deposition Policies for Fused Multi-Material 3D Printing.” In 2023 IEEE International Conference on Robotics and Automation. IEEE, 2023.
K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, and V. Babaei, “Learning deposition policies for fused multi-material 3D printing,” in 2023 IEEE International Conference on Robotics and Automation, London, United Kingdom, 2023.
Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. 2023. Learning deposition policies for fused multi-material 3D printing. 2023 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation.
Liao, Kang, et al. “Learning Deposition Policies for Fused Multi-Material 3D Printing.” 2023 IEEE International Conference on Robotics and Automation, IEEE, 2023.
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