Robotics & Machine Learning Daily News2024,Issue(Feb.6) :22-23.DOI:10.1002/aisy.202300516

Investigators from Georgia Institute of Technology Report New Data on Robotics (Robotic Conformal Material Extrusion 3d Printing for Appending Structures On Unstructured Surfaces)

Robotics & Machine Learning Daily News2024,Issue(Feb.6) :22-23.DOI:10.1002/aisy.202300516

Investigators from Georgia Institute of Technology Report New Data on Robotics (Robotic Conformal Material Extrusion 3d Printing for Appending Structures On Unstructured Surfaces)

扫码查看

Abstract

Investigators publish new report on Robotics. According to news originating from Atlanta, Georgia, by NewsRx correspondents, research stated, “Fabrication of structures in unstructured conditions is a promising area of bolstering the application spaces of additive manufacturing (AM). One emerging application is appending structures on existing ones that may have nonplanar surfaces in unconventional orientations.” Financial support for this research came from Air Force Office of Scientific Research. Our news journalists obtained a quote from the research from the Georgia Institute of Technology, “However, extrusion-based AM techniques are limited to printing on structured, planar environments with a fixed single-nozzle direction. Herein, the authors present a dexterous conformal material extrusion printing method using a six-axis robotic arm capable of constructing complex parts onto highly unstructured surfaces with rough topographies. The manufacturing method employs a custom algorithm that generates layers consisting of 3D spatial coordinates of print path as well as the extrusion nozzle oriented in the normal direction of the substrate, thereby enabling conformal motion of the extrusion nozzle to the unstructured surface. The capabilities of the surface-informed robotic conformal 3D printing method to fabricate structures on surfaces with a variety of topographies in unconventional orientations are demonstrated. Finally, via addition of deposited conductive paths, a high-strength, functional reinforcement capable of in situ deformation monitoring is appended. This work has the potential for reconstructing, repairing, and reinforcing existing structures in human-limited or inaccessible spaces. Integration of functional elements can also enable in situ sensing, monitoring, and self-diagnosis. This work presents a dexterous conformal material extrusion printing method using a six-axis robotic arm capable of constructing complex parts onto unstructured surfaces with rough topographies.”

Key words

Atlanta/Georgia/United States/North and Central America/Emerging Technologies/Machine Learning/Robotics/Robots/Georgia Institute of Technology

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
参考文献量46
段落导航相关论文