| _id |
acadia17_164 |
| id |
acadia17_164 |
| authors |
Brugnaro, Giulio; Hanna, Sean |
| year |
2017 |
| title |
Adaptive Robotic Training Methods for Subtractive Manufacturing |
| source |
ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 164-169 |
| doi |
https://doi.org/10.52842/conf.acadia.2017.164
|
| summary |
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. |
| keywords |
design methods; information processing; construction; robotics; ai & machine learning; digital craft; manual craft |
| series |
ACADIA |
| email |
|
| last changed |
2022/06/07 07:52 |
