UTCS Artificial Intelligence
courses
talks/events
demos
people
projects
publications
software/data
labs
areas
admin
Functional Generative Design of Mechanisms with Recurrent Neural Networks and Novelty Search (2019)
Cameron R. Wolfe
,
Cem C. Tutum
and
Risto Miikkulainen
Consumer-grade 3D printers have made it easier to fabricate aesthetic objects and static assemblies, opening the door to automated design of such objects. However, while static designs are easily produced with 3D printing, functional designs with moving parts are more difficult to generate: The search space is too high-dimensional, the resolution of the 3D-printed parts is not adequate, and it is difficult to predict the physical behavior of imperfect 3D-printed mechanisms. An example challenge is to produce a diverse set of reliable and effective gear mechanisms that could be used after production without extensive post-processing. To meet this challenge, an indirect encoding based on a Recurrent Neural Network (RNN) is created and evolved using novelty search. The elite solutions of each generation are 3D printed to evaluate their functional performance on a physical test platform. The system is able to discover sequential design rules that are difficult to discover with other methods. Compared to direct encoding evolved with Genetic Algorithms (GAs), its designs are geometrically more diverse and functionally more effective. It therefore forms a promising foundation for the generative design of 3D-printed, functional mechanisms.
View:
PDF
Citation:
To Appear In
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019)
, pp. 7, Prague, Czech Republic, July 2019.
Bibtex:
@inproceedings{tutum:gecco19, title={Functional Generative Design of Mechanisms with Recurrent Neural Networks and Novelty Search}, author={Cameron R. Wolfe and Cem C. Tutum and Risto Miikkulainen}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019)}, month={July}, address={Prague, Czech Republic}, pages={7}, url="http://www.cs.utexas.edu/users/ai-lab?tutum:gecco19", year={2019} }
People
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
Cem C Tutum
Formerly affiliated Research Scientist
tutum [at] cs utexas edu
Cameron R. Wolfe
Undergraduate Alumni
wolfe cameron [at] utexas edu
Areas of Interest
Evolutionary Computation
Memory
Neuroevolution
Labs
Neural Networks