rl-toolpath-planner.github.io - Learning Based Toolpath Planner on Diverse Graphs for 3D Printing

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Description: Learning Based Toolpath Planner on Diverse Graphs for 3D Printing

3d printing (1263) rl (50) toolpath (2)

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1. The University of Manchester, United Kingdom 2. Boston University, United States 3. The Chinese University of Hong Kong, Hong Kong SAR., China * Equal contribution of the first two authors † Corresponding author (Email: [email protected])

We presents an efficient reinforcement learning (RL) based planner for computing optimized 3D printing toolpaths, which can work on graphs on large scales by constructing the state space on-the-fly. The planner can cover different 3D printing applications by defining their corresponding reward functions and state spaces. Toolpath generation problems in wire-frame printing, continuous fiber printing, and metallic printing are selected here to demonstrate generality. The resultant toolpaths have been applied

Applications in computing optimized toolpaths for 3D printing problems of wire-frame models, the continuous fiber reinforced layer for Carbon Fiber Reinforced Thermoplastics (CFRTP), and Laser Powder Bed Fusion (LPBF) based metal printing. Given input graphs, our planner can generate toolpaths optimized according to manufacturing objectives. The toolpaths have been tested in physical experiments to produce the results. Three different parts of the toolpath are visualized as red, green, and blue arrows.

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