GLSO: Grammar-guided Latent Space Optimization for Sample-efficient Robot Design Automation

1 code implementation • 23 Sep 2022 • Jiaheng Hu, Julian Whiman, Howie Choset

In this work, we present Grammar-guided Latent Space Optimization (GLSO), a framework that transforms design automation into a low-dimensional continuous optimization problem by training a graph variational autoencoder (VAE) to learn a mapping between the graph-structured design space and a continuous latent space.

Bayesian Optimization valid