Re/Learning the Wheel. Methods to Utilize Neural Networks as Design Tools for Doubly Curved Metal Surfaces

Rossi, Gabriella; Nicholas, Paul

doi:10.52842/conf.acadia.2018.146

Cited by 13 publications

(8 citation statements)

References 7 publications

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“…Another area of metalworking was also identified where we found study cases of traditional blacksmithing in which manual skill and experience with different tools, hammer, craft former, English wheel, and turning lathe for the manufacture of metal artifacts are shown (Russo B ., Cleaver, Allwood, & Loukaides, 2022) (Ilangovan, Monfared, & Jackson, 2016) (Rossi & Nicholas, 2018) (Bowen, Music, Erdinc, & Shokrani, 2021) (Russo, Cleaver, & Allwood, 2019) Similarly, we found a case study on manual skill in polishing metal parts (Kalt, Monfared, & Jackson, 2016). In addition, two particular case studies were identified on the skills for manual roughing of leather parts for shoe assembly, since it is an operation that requires great skill and experience on the part of the operator (Pedrocchi, Villagrossi, Cenat, & Tosatti , 2015).…”

Section: Robots and Automationsupporting

confidence: 64%

– The European Conference on Arts, Design and Education 2022 Official Conference Proceedings

2022

ECADE Official Conference Proceedings

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Climate change is impacting on all aspects of contemporary life. Many artists provide a compelling vision for speculative futures, awakening a creative consciousness using imagined worldviews. This paper presents my practice-based research that aims to establish how visual art can engage with issues-based concepts and ideologies through the presentation, re-presentation, and interpretation as a framework for engaging with climate change issues and realigning society to sustainable futures. This paper takes theory, and artistic practice as methods means to respond to themes and issues of climate change. In the context of practical research, the arts-based approach and art theory research alternate between planning, theoretical research, practical action, reflection, and evaluation. Through digital art, this study creates a discursive space that relates to daily life, where people can deeply understand the interconnecting relationships between humans and the planet; simultaneously, it also shows people an achievable ecological future and encourages people to think and find an existence conducive to all. This existence is not the present, but a possibility for human beings to explore the future through the reshaping and reimagining of the present.

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Section: Robots and Automationsupporting

confidence: 64%

– The European Conference on Arts, Design and Education 2022 Official Conference Proceedings

2022

ECADE Official Conference Proceedings

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“…The AI model recalibrates at every iteration, without having the final configuration explicitly preprogrammed, converging towards an approximation that is deemed good enough, yet not error-free (Rossi and Nicholas 2018).…”

Section: Results Evaluationmentioning

confidence: 99%

“…Machine learning has proven capable of translating complex fabrication systems and crafts into robotic toolpaths, as shown by Rossi and Nicholas's work with the English Wheel (Rossi and Nicholas 2018) as well as the work of Brugnaro and Hanna with wood chisels (Brugnaro and Hanna 2017). This research project pushes the state of the art of training a neural network for robotic fabrication by using a surrogate digital model rather than directly analyzing the motions of a master craftsperson or digitizing produced samples.…”

Section: Introductionmentioning

confidence: 99%

Imaginary Vessels

Quinteros,

Rossi,

Shawqy

et al. 2021

ACADIA Proceedings

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Clay is one of the foundational materials in art and architecture, traced in the development of mud walls and adobe structures, and showcased in utilitarian and ornamental pottery. Wheel throwing is the process of shaping clay mainly into symmetrical objects, a complex craft in which the master potter has the knowledge and skill to manipulate the clay into the fi nal design of various physical objects. This project explores how machine learning can be used to translate the richness and complexity of wheel throwing for digital fabrication.In this paper we present a surrogate digital dataset for robotic fabrication and geometric prediction used to train neural networks and provide a bridge between digital fabrication and handcraft. We report on the parametric model that abstracts wheel throwing as the interaction between a rotating mass and a given set of forces, as well as on data wrangling methods, dataset composition considerations, and training methodology. We present two models, one in which geometry is predicted based on a given set of forces, and a second in which forces are predicted based on a given geometry. Lastly, we give a critical assessment of the predictions of both networks and discuss future steps.

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“…Our approach instead utilises clean and controlled digitally generated data, coupled with live joint position streaming from the robot controller when the robot is guided in MCM by the user. Using a data handling, prepping and wrapping approach similar to that developed by (Rossi and Nicholas 2018), we are able to control the workflow directly from within the design environment.…”

Section: A Hybird Robotic Programming Approach Neural-network Meet Hu...mentioning

confidence: 99%

Haptic Learning - Towards Neural-Network-based adaptive Cobot Path-Planning for unstructured spaces

Rossi¹,

Nicholas²

2019

Proceedings of the 37th International Conference on Education and Research in Computer Aided Architectural Design in Europe (eC

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Re/Learning the Wheel. Methods to Utilize Neural Networks as Design Tools for Doubly Curved Metal Surfaces

Cited by 13 publications

References 7 publications

– The European Conference on Arts, Design and Education 2022 Official Conference Proceedings

– The European Conference on Arts, Design and Education 2022 Official Conference Proceedings

Imaginary Vessels

Haptic Learning - Towards Neural-Network-based adaptive Cobot Path-Planning for unstructured spaces

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