Robotic Depowdering for Additive Manufacturing Via Pose Tracking

TL;DR

This paper presents a real-time vision-based robotic system for automated depowdering in additive manufacturing, capable of handling various part shapes without pre-depowdering, significantly improving efficiency and adaptability.

Contribution

The authors introduce a novel robotic depowdering system with a real-time pose-tracking visual perception module that adapts to different part geometries without pre-depowdering.

Findings

System removes unfused powder effectively without damaging parts.

Pose-tracking runs at 60 FPS on a laptop CPU.

System works on various shapes without pre-depowdering.

Abstract

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.