| Autor: |
Chaudhary, Gaurav, Christ, Stephanie, Hart, A John, Mahadevan, L |
| Rok vydání: |
2023 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
The range and speed of direct ink writing, the workhorse of 3d and 4d printing, is limited by the practice of liquid extrusion from a nozzle just above the surface to prevent instabilities to cause deviations from the required print path. But what if could harness the ``fluid rope trick", whence a thin stream of viscous fluid falling from a height spontaneously folds or coils, to write specified patterns on a substrate? Using Deep Reinforcement Learning we control the motion of the extruding nozzle and thence the fluid patterns that are deposited on the surface. The learner (nozzle) repeatedly interacts with the environment (a viscous filament simulator), and improves its strategy using the results of this experience. We demonstrate the results in an experimental setting where the learned motion control instructions are used to drive a viscous jet to accomplish complex tasks such as cursive writing and Pollockian paintings. |
| Databáze: |
arXiv |
| Externí odkaz: |
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