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

机译:用于多轴机器化添加剂制造的多轴Robotized Addive制造的层 - 逐层生成

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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.
机译:这项工作侧重于使用6轴机器人定向能量沉积(DED)的添加剂制造。目的是在联合空间中产生优化的轨迹,考虑到具有同轴沉积系统的旋转部分的轴冗余。为了实现这一目标,提出了一种与轨迹约束优化耦合的新的逐层方法。优化结果与非优化的轨迹和点对点优化的轨迹相比,理论上是相比的。使用PLA挤出系统通过实验在6轴机器人上进行优化轨迹的逐层生成。实验结果表明,应用于旋转部分的逐层轨迹优化策略提供了更好的几何精度,同时与非优化解决方案相比提高了制造装置的效率。

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