论文标题
通过姿势跟踪进行增材制造的机器人脱皮
Robotic Depowdering for Additive Manufacturing Via Pose Tracking
论文作者
论文摘要
随着基于粉末的添加剂制造的快速开发,DepeDdering是去除覆盖3D打印零件的未使用粉末的过程,已成为进一步提高其生产力的主要瓶颈。传统的手动缩减非常耗时且昂贵,并且一些先前的自动化系统要么需要预先替代或缺乏对不同3D打印零件的适应性。为了解决这些问题,我们引入了一个机器人系统,该机器人系统会自动从3D打印零件的表面上去除未使用的粉末。关键组件是一个视觉感知系统,该系统由一个姿势跟踪模块组成,该模块可实时跟踪6D姿势的粉末叠加零件,以及一个估计缩减完成百分比的进度估计模块。跟踪模块可以在最高60 fps的笔记本电脑CPU上有效运行。实验表明,我们的缩减系统可以从各种3D打印零件的表面上除去未加入的粉末,而不会造成任何损坏。据我们所知,这是第一个基于视觉的机器人拔空系统之一,它适应各种形状的部分而无需预多供电。
With the rapid development of powder-based additive manufacturing, depowdering, a process of removing unfused powder that covers 3D-printed parts, has become a major bottleneck to further improve its productiveness. Traditional manual depowdering is extremely time-consuming and costly, and some prior automated systems either require pre-depowdering or lack adaptability to different 3D-printed parts. To solve these problems, we introduce a robotic system that automatically removes unfused powder from the surface of 3D-printed parts. The key component is a visual perception system, which consists of a pose-tracking module that tracks the 6D pose of powder-occluded parts in real-time, and a progress estimation module that estimates the depowdering completion percentage. The tracking module can be run efficiently on a laptop CPU at up to 60 FPS. Experiments show that our depowdering system can remove unfused powder from the surface of various 3D-printed parts without causing any damage. To the best of our knowledge, this is one of the first vision-based robotic depowdering systems that adapt to parts with various shapes without the need for pre-depowdering.