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https://github.com/ytakzk/generative_modelling_with_design_constraints

Reinforcement learning for furniture generation
https://github.com/ytakzk/generative_modelling_with_design_constraints

architectural-design generative-art generative-model machine-learning object-generation reinforcement-learning

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Reinforcement learning for furniture generation

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## Generative Modelling with Design Constraints

Generative design has been explored in architecture to produce unprecedented geometries, however, in most cases, design constraints are limited during the design process.
Limitations of existing generative design strategies include topological inconsistencies of the output geometries, dense design outputs, as the format used is often voxels or point clouds, and finally out-of-scope design constraints.
In order to overcome such shortcomings, a novel reinforcement learning (RL) framework is explored in order to design a series of furniture with embedded design and fabrication constraints.

![LEGO Block animation](https://github.com/ytakzk/generative_modelling_with_design_constraints/raw/master/img/animation.gif)

## Demo

You can try it out on our web application [here](https://rl.ytakzk.me/)!

![Screenshot](https://github.com/ytakzk/generative_modelling_with_design_constraints/raw/master/img/webapp.jpg)

## Dependences

* TensorFlow 1.14.0
* Stable Baselines 2.7.0
* OpenAI Gym 0.14.0
* Trimesh 3.2.13
* OpenMPI 3.2.1

## Works

![LEGO](https://github.com/ytakzk/generative_modelling_with_design_constraints/raw/master/img/lego.jpg)
![Voxel](https://github.com/ytakzk/generative_modelling_with_design_constraints/raw/master/img/voxel.jpg)