Development of a Robotic System for Automated Decaking of 3D-Printed Parts
March 11, 2020 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Huy Nguyen, Nicholas Adrian, Joyce Lim Xin Yan, Jonathan M. Salfity, William Allen, Quang-Cuong Pham
arXiv ID
2003.05115
Category
cs.RO: Robotics
Citations
13
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
Abstract
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.
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