Towards Visual Feedback Loops for Robot-Controlled Additive Manufacturing

Sutjipto, S; Tish, D; Paul, G; Vidal Calleja, T; Schork, T

Towards Visual Feedback Loops for Robot-Controlled Additive Manufacturing

Sutjipto, S Tish, D

Paul, G

Vidal Calleja, T

Schork, T

Permalink

Publisher:: Springer
Publication Type:: Conference Proceeding
Citation:: Robotic Fabrication in Architecture, Art and Design 2018, 2019, pp. 85 - 97
Issue Date:: 2019

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Accepted Manuscript versionAdobe PDF (692.16 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Sutjipto, S	en_US
dc.contributor.author	Tish, D https://orcid.org/0000-0003-3776-9748	en_US
dc.contributor.author	Paul, G https://orcid.org/0000-0002-3478-0020	en_US
dc.contributor.author	Vidal Calleja, T https://orcid.org/0000-0002-5763-9644	en_US
dc.contributor.author	Schork, T https://orcid.org/0000-0002-4583-2439	en_US
dc.contributor.editor	Willmann, J	en_US
dc.contributor.editor	Block, P	en_US
dc.contributor.editor	Hutter, M	en_US
dc.contributor.editor	Byrne, K	en_US
dc.contributor.editor	Schork, T https://orcid.org/0000-0002-4583-2439	en_US
dc.date	2018-09-12	en_US
dc.date.issued	2019	en_US
dc.identifier.citation	Robotic Fabrication in Architecture, Art and Design 2018, 2019, pp. 85 - 97	en_US
dc.identifier.isbn	978-3-319-92293-5	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132032
dc.description.abstract	Robotic additive manufacturing methods have enabled the design and fabrication of novel forms and material systems that represent an important step forward for architectural fabrication. However, a common problem in additive manufacturing is to predict and incorporate the dynamic behavior of the material that is the result of the complex confluence of forces and material properties that occur during fabrication. While there have been some approaches towards verification systems, to date most robotic additive manufacturing processes lack verification to ensure deposition accuracy. Inaccuracies, or in some instances critical errors, can occur due to robot dynamics, material self-deflection, material coiling, or timing shifts in the case of multi-material prints. This paper addresses that gap by presenting an approach that uses vision-based sensing systems to assist robotic additive manufacturing processes. Using online image analysis techniques, occupancy maps can be created and updated during the fabrication process to document the actual position of the previously deposited material. This development is an intermediary step towards closed-loop robotic control systems that combine workspace sensing capabilities with decision-making algorithms to adjust toolpaths to correct for errors or inaccuracies if necessary. The occupancy grid map provides a complete representation of the print that can be analyzed to determine various key aspects, such as, print quality, extrusion diameter, adhesion between printed parts, and intersections within the meshes. This valuable quantitative information regarding system robustness can be used to influence the system’s future actions. This approach will help ensure consistent print quality and sound tectonics in robotic additive manufacturing processes, improving on current techniques and extending the possibilities of robotic fabrication in architecture.	en_US
dc.publisher	Springer	en_US
dc.relation.ispartof	Robotic Fabrication in Architecture, Art and Design 2018	en_US
dc.relation.ispartof	Robotic Fabrication in Architecture, Art and Design	en_US
dc.relation.isbasedon	10.1007/978-3-319-92294-2_7	en_US
dc.rights	This is a post-peer-review, pre-copyedit version of an article published in Robotic Fabrication in Architecture, Art and Design. The final authenticated version is available online at: https://dx.doi.org/10.1007/978-3-319-92294-2_7.	en_US
dc.rights	This is a post-peer-review, pre-copyedit version of an article published in Robotic Fabrication in Architecture, Art and Design 2018. The final authenticated version is available online at: https://dx.doi.org/10.1007/978-3-319-92294-2_7.	en_US
dc.title	Towards Visual Feedback Loops for Robot-Controlled Additive Manufacturing	en_US
dc.type	Conference Proceeding
utslib.location	Cham, Switzerland	en_US
utslib.location.activity	Zurich	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	1203 Design Practice and Management	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Architecture
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.finish-date	2018-09-14	en_US
pubs.place-of-publication	Cham, Switzerland	en_US
pubs.publication-status	Published	en_US
pubs.start-date	2018-09-12	en_US

Abstract:

Robotic additive manufacturing methods have enabled the design and fabrication of novel forms and material systems that represent an important step forward for architectural fabrication. However, a common problem in additive manufacturing is to predict and incorporate the dynamic behavior of the material that is the result of the complex confluence of forces and material properties that occur during fabrication. While there have been some approaches towards verification systems, to date most robotic additive manufacturing processes lack verification to ensure deposition accuracy. Inaccuracies, or in some instances critical errors, can occur due to robot dynamics, material self-deflection, material coiling, or timing shifts in the case of multi-material prints. This paper addresses that gap by presenting an approach that uses vision-based sensing systems to assist robotic additive manufacturing processes. Using online image analysis techniques, occupancy maps can be created and updated during the fabrication process to document the actual position of the previously deposited material. This development is an intermediary step towards closed-loop robotic control systems that combine workspace sensing capabilities with decision-making algorithms to adjust toolpaths to correct for errors or inaccuracies if necessary. The occupancy grid map provides a complete representation of the print that can be analyzed to determine various key aspects, such as, print quality, extrusion diameter, adhesion between printed parts, and intersections within the meshes. This valuable quantitative information regarding system robustness can be used to influence the system’s future actions. This approach will help ensure consistent print quality and sound tectonics in robotic additive manufacturing processes, improving on current techniques and extending the possibilities of robotic fabrication in architecture.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/132032