Adaptive Robotic Training Methods for Subtractive Manufacturing (2017)
article⁄Adaptive Robotic Training Methods for Subtractive Manufacturing (2017)
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, machinelearning 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 nonstandard fabrication methods and a more effective use of material affordances.
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| Year |
2017 |
| Authors |
Brugnaro, Giulio; Hanna, Sean. |
| Issue |
ACADIA 2017: DISCIPLINES & DISRUPTION |
| Pages |
164-169 |
| Library link |
N/A |
| Entry filename |
adaptive-robotic-training-methods-subtractive-manufacturing |
