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bin
fig
openrave
output
urdf
.gitignore
LICENSE
README.md
baxter_openrave.py
baxter_vae_assoc_writer.py
baxter_writer.py
dataset.py
deconv.py
drawing_pad.py
pygcem.py
pyrbf_funcapprox.py
pytrajkin_rxzero.py
utils.py
vae_assoc.py
vae_assoc_model_viewer.py
vae_assoc_ujichar_img_jnt.py
writing_image_reader.py

README.md

vae_assoc

Variational Auto-encoders factored with enforced identity of the latent variables. See reference:

Yin, H., Melo, F. S., Billard, A. and Paiva, A. Associate Latent Encodings in Learning from Demonstrations. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17). San Francisco, California, USA.

Downloading data and a model example

$ cd bin
$ ./download_data.sh
$ cd ../output
$ ./download_model.sh

Video demo

Observe associated encodings of letter images and dynamical writing motion

$ python vae_assoc_model_viewer.py

Inference of writing motion from a letter image

Launch roscore for exchanging messages.

$ roscore

In another terminal, start the the GUI and the rendering simulator

$ python baxter_openrave.py &
$ python baxter_vae_assoc_writer.py

Some main dependencies

Mandatory:

Tensorflow (>=0.8.0)

Optional (for robot motion, messaging and rendering purposes):

PyQT

ROS

OpenRAVE

baxter_pykdl