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Layer-by-layer generation of optimized joint trajectory for multi-axis robotized additive manufacturing of parts of revolution

Abstract : This work focuses on additive manufacturing by Directed Energy Deposition (DED) using a 6-axis robot. The objective is to generate an optimized trajectory in the joint space, taking into account axis redundancy for parts of revolution produced with a coaxial deposition system. To achieve this goal, a new layer-by-layer method coupled with a trajectory constrained optimization is presented. The optimization results are theoretically compared to a non-optimized trajectory and a point-by-point optimized trajectory. The layer-by-layer generation of optimized trajectories is validated experimentally on a 6-axis robot using a PLA extrusion system. Experimental results show that the layer-by-layer trajectory optimization strategy applied to parts of revolution provides better geometrical accuracy while improving the efficiency of the manufacturing device compared to non-optimized solutions.
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https://hal.archives-ouvertes.fr/hal-02509891
Contributor : Sébastien Campocasso <>
Submitted on : Wednesday, August 26, 2020 - 10:11:47 AM
Last modification on : Friday, October 2, 2020 - 12:25:39 PM
Long-term archiving on: : Friday, November 27, 2020 - 12:24:16 PM

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Maxime Chalvin, Sébastien Campocasso, Vincent Hugel, Thomas Baizeau. Layer-by-layer generation of optimized joint trajectory for multi-axis robotized additive manufacturing of parts of revolution. Robotics and Computer-Integrated Manufacturing, Elsevier, 2020, 65 (101960), pp.1-11. ⟨10.1016/j.rcim.2020.101960⟩. ⟨hal-02509891⟩

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