===== CVAE Exploration Data =====
This page contains the accompanying data for the CVAE Exploration Planning project. The code to train our models and run a planner is available at [[https://github.com/ethz-asl/cvae_exploration_planning]]. The paper preprint is available on [[https://arxiv.org/abs/2202.13715 | ArXiv]]:

Schmid, Lukas, and Ni, Chao, et al. "Fast and Compute-efficient Sampling-based Local Exploration Planning via Distribution Learning", in IEEE Robotics and Automation Letters (RA-L), 2022.

=== Data Layout ===
The following files are provided (# short description). Additional processing and use tools are available on [[https://github.com/ethz-asl/panoptic_mapping |github]].

Data:
  * CVAE_dataset.npy # Numpy data containing all our local maps with the best actions identified by the teacher planner as supervision signal. Used to train or CVAE models.
  * CNN_dataset.npy # Numpy data containing local maps with random actions used to train the CNN models.
  * test_worlds.zip # Directory containing all separate test worlds used in our experiments.
    * <environment>_<no>.p # Pickle file containing the test world.
    * <environment>_<no>.txt #Text file containing the initial position as [x, y, yaw] used in our experiments.

==== Download ====
[[http://robotics.ethz.ch/~asl-datasets/2022_CVAE_Exploration_Planning|Data Repository]]

[[http://robotics.ethz.ch/~asl-datasets/2022_CVAE_Exploration_Planning/CVAE_dataset.npy|CVAE_dataset.npy (326.4 MB)]]

[[http://robotics.ethz.ch/~asl-datasets/2022_CVAE_Exploration_Planning/CNN_dataset.npy|CNN_dataset.npy (1.0 GB)]]

[[http://robotics.ethz.ch/~asl-datasets/2022_CVAE_Exploration_Planning/test_worlds.zip|test_worlds.zip (56.5 KB)]]