论文标题
开发用于3D打印零件的自动脱脱的机器人系统
Development of a Robotic System for Automated Decaking of 3D-Printed Parts
论文作者
论文摘要
随着3D打印作为一种竞争性质量制造方法的迅速上升，手动“破坏” - 即去除粘在3D打印部分的残留粉末已成为一种显着的瓶颈。在这里，我们首次介绍了我们的知识，这是一种用于自动脱落3D打印零件的机器人系统。结合了3D感知，智能机械设计，运动计划和工业机器人的力量控制的深度学习，我们开发了一个可以自动以快速有效的方式脱落零件的系统。通过对由多喷气融合打印机印刷的零件进行的一系列破坏实验，我们证明了机器人脱落对基于3D打印的质量制造的可行性。
With the rapid rise of 3D-printing as a competitive mass manufacturing method, manual "decaking" - i.e. removing the residual powder that sticks to a 3D-printed part - has become a significant bottleneck. Here, we introduce, for the first time to our knowledge, a robotic system for automated decaking of 3D-printed parts. Combining Deep Learning for 3D perception, smart mechanical design, motion planning, and force control for industrial robots, we developed a system that can automatically decake parts in a fast and efficient way. Through a series of decaking experiments performed on parts printed by a Multi Jet Fusion printer, we demonstrated the feasibility of robotic decaking for 3D-printing-based mass manufacturing.
