Brugnaro, G;
Hanna, S;
(2017)
Adaptive Robotic Training Methods for Subtractive Manufacturing.
In:
Acadia 2017 Disciplines & Disruption: Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture.
(pp. pp. 164-169).
Acadia Publishing Company: Cambridge, MA, USA.
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Abstract
This paper presents the initial developments of a method to train an adaptive robotic system for subtractive manufacturing with timber, based on sensor feedback, machine-learning procedures and material explorations. The methods were evaluated in a series of tests where the trained networks were successfully used to predict fabrication parameters for simple cutting operations with chisels and gouges. The results suggest potential benefits for non-standard fabrication methods and a more effective use of material affordances.
Type: | Proceedings paper |
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Title: | Adaptive Robotic Training Methods for Subtractive Manufacturing |
Event: | ACADIA 2017: Disciplines & Disruption |
Location: | Cambridge, MA |
Dates: | 02 November 2017 - 04 November 2017 |
ISBN-13: | 978-0-692-96506-1 |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | http://papers.cumincad.org/cgi-bin/works/Search?se... |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Design methods, information processing, construction, robotics, ai & machine learning, digital craft, manual craft |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > The Bartlett School of Architecture |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10032548 |
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